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block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Budget Fair Queueing (BFQ) I/O scheduler.
*
* Based on ideas and code from CFQ:
* Copyright (C) 2003 Jens Axboe <axboe@kernel.dk>
*
* Copyright (C) 2008 Fabio Checconi <fabio@gandalf.sssup.it>
* Paolo Valente <paolo.valente@unimore.it>
*
* Copyright (C) 2010 Paolo Valente <paolo.valente@unimore.it>
* Arianna Avanzini <avanzini@google.com>
*
* Copyright (C) 2017 Paolo Valente <paolo.valente@linaro.org>
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License as
* published by the Free Software Foundation; either version 2 of the
* License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* BFQ is a proportional-share I/O scheduler, with some extra
* low-latency capabilities. BFQ also supports full hierarchical
* scheduling through cgroups. Next paragraphs provide an introduction
* on BFQ inner workings. Details on BFQ benefits, usage and
* limitations can be found in Documentation/block/bfq-iosched.txt.
*
* BFQ is a proportional-share storage-I/O scheduling algorithm based
* on the slice-by-slice service scheme of CFQ. But BFQ assigns
* budgets, measured in number of sectors, to processes instead of
* time slices. The device is not granted to the in-service process
* for a given time slice, but until it has exhausted its assigned
* budget. This change from the time to the service domain enables BFQ
* to distribute the device throughput among processes as desired,
* without any distortion due to throughput fluctuations, or to device
* internal queueing. BFQ uses an ad hoc internal scheduler, called
* B-WF2Q+, to schedule processes according to their budgets. More
* precisely, BFQ schedules queues associated with processes. Each
* process/queue is assigned a user-configurable weight, and B-WF2Q+
* guarantees that each queue receives a fraction of the throughput
* proportional to its weight. Thanks to the accurate policy of
* B-WF2Q+, BFQ can afford to assign high budgets to I/O-bound
* processes issuing sequential requests (to boost the throughput),
* and yet guarantee a low latency to interactive and soft real-time
* applications.
*
* In particular, to provide these low-latency guarantees, BFQ
* explicitly privileges the I/O of two classes of time-sensitive
* applications: interactive and soft real-time. This feature enables
* BFQ to provide applications in these classes with a very low
* latency. Finally, BFQ also features additional heuristics for
* preserving both a low latency and a high throughput on NCQ-capable,
* rotational or flash-based devices, and to get the job done quickly
* for applications consisting in many I/O-bound processes.
*
block, bfq: stress that low_latency must be off to get max throughput The introduction of the BFQ and Kyber I/O schedulers has triggered a new wave of I/O benchmarks. Unfortunately, comments and discussions on these benchmarks confirm that there is still little awareness that it is very hard to achieve, at the same time, a low latency and a high throughput. In particular, virtually all benchmarks measure throughput, or throughput-related figures of merit, but, for BFQ, they use the scheduler in its default configuration. This configuration is geared, instead, toward a low latency. This is evidently a sign that BFQ documentation is still too unclear on this important aspect. This commit addresses this issue by stressing how BFQ configuration must be (easily) changed if the only goal is maximum throughput. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-09 17:54:23 +07:00
* NOTE: if the main or only goal, with a given device, is to achieve
* the maximum-possible throughput at all times, then do switch off
* all low-latency heuristics for that device, by setting low_latency
* to 0.
*
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
* BFQ is described in [1], where also a reference to the initial, more
* theoretical paper on BFQ can be found. The interested reader can find
* in the latter paper full details on the main algorithm, as well as
* formulas of the guarantees and formal proofs of all the properties.
* With respect to the version of BFQ presented in these papers, this
* implementation adds a few more heuristics, such as the one that
* guarantees a low latency to soft real-time applications, and a
* hierarchical extension based on H-WF2Q+.
*
* B-WF2Q+ is based on WF2Q+, which is described in [2], together with
* H-WF2Q+, while the augmented tree used here to implement B-WF2Q+
* with O(log N) complexity derives from the one introduced with EEVDF
* in [3].
*
* [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
* Scheduler", Proceedings of the First Workshop on Mobile System
* Technologies (MST-2015), May 2015.
* http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf
*
* [2] Jon C.R. Bennett and H. Zhang, "Hierarchical Packet Fair Queueing
* Algorithms", IEEE/ACM Transactions on Networking, 5(5):675-689,
* Oct 1997.
*
* http://www.cs.cmu.edu/~hzhang/papers/TON-97-Oct.ps.gz
*
* [3] I. Stoica and H. Abdel-Wahab, "Earliest Eligible Virtual Deadline
* First: A Flexible and Accurate Mechanism for Proportional Share
* Resource Allocation", technical report.
*
* http://www.cs.berkeley.edu/~istoica/papers/eevdf-tr-95.pdf
*/
#include <linux/module.h>
#include <linux/slab.h>
#include <linux/blkdev.h>
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#include <linux/cgroup.h>
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
#include <linux/elevator.h>
#include <linux/ktime.h>
#include <linux/rbtree.h>
#include <linux/ioprio.h>
#include <linux/sbitmap.h>
#include <linux/delay.h>
#include "blk.h"
#include "blk-mq.h"
#include "blk-mq-tag.h"
#include "blk-mq-sched.h"
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
#include "bfq-iosched.h"
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
#define BFQ_BFQQ_FNS(name) \
void bfq_mark_bfqq_##name(struct bfq_queue *bfqq) \
{ \
__set_bit(BFQQF_##name, &(bfqq)->flags); \
} \
void bfq_clear_bfqq_##name(struct bfq_queue *bfqq) \
{ \
__clear_bit(BFQQF_##name, &(bfqq)->flags); \
} \
int bfq_bfqq_##name(const struct bfq_queue *bfqq) \
{ \
return test_bit(BFQQF_##name, &(bfqq)->flags); \
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
BFQ_BFQQ_FNS(just_created);
BFQ_BFQQ_FNS(busy);
BFQ_BFQQ_FNS(wait_request);
BFQ_BFQQ_FNS(non_blocking_wait_rq);
BFQ_BFQQ_FNS(fifo_expire);
BFQ_BFQQ_FNS(idle_window);
BFQ_BFQQ_FNS(sync);
BFQ_BFQQ_FNS(IO_bound);
BFQ_BFQQ_FNS(in_large_burst);
BFQ_BFQQ_FNS(coop);
BFQ_BFQQ_FNS(split_coop);
BFQ_BFQQ_FNS(softrt_update);
#undef BFQ_BFQQ_FNS \
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Expiration time of sync (0) and async (1) requests, in ns. */
static const u64 bfq_fifo_expire[2] = { NSEC_PER_SEC / 4, NSEC_PER_SEC / 8 };
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Maximum backwards seek (magic number lifted from CFQ), in KiB. */
static const int bfq_back_max = 16 * 1024;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Penalty of a backwards seek, in number of sectors. */
static const int bfq_back_penalty = 2;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Idling period duration, in ns. */
static u64 bfq_slice_idle = NSEC_PER_SEC / 125;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Minimum number of assigned budgets for which stats are safe to compute. */
static const int bfq_stats_min_budgets = 194;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Default maximum budget values, in sectors and number of requests. */
static const int bfq_default_max_budget = 16 * 1024;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/*
* Async to sync throughput distribution is controlled as follows:
* when an async request is served, the entity is charged the number
* of sectors of the request, multiplied by the factor below
*/
static const int bfq_async_charge_factor = 10;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Default timeout values, in jiffies, approximating CFQ defaults. */
const int bfq_timeout = HZ / 8;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
static struct kmem_cache *bfq_pool;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Below this threshold (in ns), we consider thinktime immediate. */
#define BFQ_MIN_TT (2 * NSEC_PER_MSEC)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* hw_tag detection: parallel requests threshold and min samples needed. */
#define BFQ_HW_QUEUE_THRESHOLD 4
#define BFQ_HW_QUEUE_SAMPLES 32
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
#define BFQQ_SEEK_THR (sector_t)(8 * 100)
#define BFQQ_SECT_THR_NONROT (sector_t)(2 * 32)
#define BFQQ_CLOSE_THR (sector_t)(8 * 1024)
#define BFQQ_SEEKY(bfqq) (hweight32(bfqq->seek_history) > 32/8)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Min number of samples required to perform peak-rate update */
#define BFQ_RATE_MIN_SAMPLES 32
/* Min observation time interval required to perform a peak-rate update (ns) */
#define BFQ_RATE_MIN_INTERVAL (300*NSEC_PER_MSEC)
/* Target observation time interval for a peak-rate update (ns) */
#define BFQ_RATE_REF_INTERVAL NSEC_PER_SEC
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* Shift used for peak rate fixed precision calculations. */
#define BFQ_RATE_SHIFT 16
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/*
* By default, BFQ computes the duration of the weight raising for
* interactive applications automatically, using the following formula:
* duration = (R / r) * T, where r is the peak rate of the device, and
* R and T are two reference parameters.
* In particular, R is the peak rate of the reference device (see below),
* and T is a reference time: given the systems that are likely to be
* installed on the reference device according to its speed class, T is
* about the maximum time needed, under BFQ and while reading two files in
* parallel, to load typical large applications on these systems.
* In practice, the slower/faster the device at hand is, the more/less it
* takes to load applications with respect to the reference device.
* Accordingly, the longer/shorter BFQ grants weight raising to interactive
* applications.
*
* BFQ uses four different reference pairs (R, T), depending on:
* . whether the device is rotational or non-rotational;
* . whether the device is slow, such as old or portable HDDs, as well as
* SD cards, or fast, such as newer HDDs and SSDs.
*
* The device's speed class is dynamically (re)detected in
* bfq_update_peak_rate() every time the estimated peak rate is updated.
*
* In the following definitions, R_slow[0]/R_fast[0] and
* T_slow[0]/T_fast[0] are the reference values for a slow/fast
* rotational device, whereas R_slow[1]/R_fast[1] and
* T_slow[1]/T_fast[1] are the reference values for a slow/fast
* non-rotational device. Finally, device_speed_thresh are the
* thresholds used to switch between speed classes. The reference
* rates are not the actual peak rates of the devices used as a
* reference, but slightly lower values. The reason for using these
* slightly lower values is that the peak-rate estimator tends to
* yield slightly lower values than the actual peak rate (it can yield
* the actual peak rate only if there is only one process doing I/O,
* and the process does sequential I/O).
*
* Both the reference peak rates and the thresholds are measured in
* sectors/usec, left-shifted by BFQ_RATE_SHIFT.
*/
static int R_slow[2] = {1000, 10700};
static int R_fast[2] = {14000, 33000};
/*
* To improve readability, a conversion function is used to initialize the
* following arrays, which entails that they can be initialized only in a
* function.
*/
static int T_slow[2];
static int T_fast[2];
static int device_speed_thresh[2];
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
#define RQ_BIC(rq) ((struct bfq_io_cq *) (rq)->elv.priv[0])
#define RQ_BFQQ(rq) ((rq)->elv.priv[1])
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
struct bfq_queue *bic_to_bfqq(struct bfq_io_cq *bic, bool is_sync)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
return bic->bfqq[is_sync];
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bic_set_bfqq(struct bfq_io_cq *bic, struct bfq_queue *bfqq, bool is_sync)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
bic->bfqq[is_sync] = bfqq;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
struct bfq_data *bic_to_bfqd(struct bfq_io_cq *bic)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
return bic->icq.q->elevator->elevator_data;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/**
* icq_to_bic - convert iocontext queue structure to bfq_io_cq.
* @icq: the iocontext queue.
*/
static struct bfq_io_cq *icq_to_bic(struct io_cq *icq)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/* bic->icq is the first member, %NULL will convert to %NULL */
return container_of(icq, struct bfq_io_cq, icq);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/**
* bfq_bic_lookup - search into @ioc a bic associated to @bfqd.
* @bfqd: the lookup key.
* @ioc: the io_context of the process doing I/O.
* @q: the request queue.
*/
static struct bfq_io_cq *bfq_bic_lookup(struct bfq_data *bfqd,
struct io_context *ioc,
struct request_queue *q)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
if (ioc) {
unsigned long flags;
struct bfq_io_cq *icq;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
spin_lock_irqsave(q->queue_lock, flags);
icq = icq_to_bic(ioc_lookup_icq(ioc, q));
spin_unlock_irqrestore(q->queue_lock, flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
return icq;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
return NULL;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
/*
* Scheduler run of queue, if there are requests pending and no one in the
* driver that will restart queueing.
*/
void bfq_schedule_dispatch(struct bfq_data *bfqd)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
if (bfqd->queued != 0) {
bfq_log(bfqd, "schedule dispatch");
blk_mq_run_hw_queues(bfqd->queue, true);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
#define bfq_class_idle(bfqq) ((bfqq)->ioprio_class == IOPRIO_CLASS_IDLE)
#define bfq_class_rt(bfqq) ((bfqq)->ioprio_class == IOPRIO_CLASS_RT)
#define bfq_sample_valid(samples) ((samples) > 80)
/*
* Lifted from AS - choose which of rq1 and rq2 that is best served now.
* We choose the request that is closesr to the head right now. Distance
* behind the head is penalized and only allowed to a certain extent.
*/
static struct request *bfq_choose_req(struct bfq_data *bfqd,
struct request *rq1,
struct request *rq2,
sector_t last)
{
sector_t s1, s2, d1 = 0, d2 = 0;
unsigned long back_max;
#define BFQ_RQ1_WRAP 0x01 /* request 1 wraps */
#define BFQ_RQ2_WRAP 0x02 /* request 2 wraps */
unsigned int wrap = 0; /* bit mask: requests behind the disk head? */
if (!rq1 || rq1 == rq2)
return rq2;
if (!rq2)
return rq1;
if (rq_is_sync(rq1) && !rq_is_sync(rq2))
return rq1;
else if (rq_is_sync(rq2) && !rq_is_sync(rq1))
return rq2;
if ((rq1->cmd_flags & REQ_META) && !(rq2->cmd_flags & REQ_META))
return rq1;
else if ((rq2->cmd_flags & REQ_META) && !(rq1->cmd_flags & REQ_META))
return rq2;
s1 = blk_rq_pos(rq1);
s2 = blk_rq_pos(rq2);
/*
* By definition, 1KiB is 2 sectors.
*/
back_max = bfqd->bfq_back_max * 2;
/*
* Strict one way elevator _except_ in the case where we allow
* short backward seeks which are biased as twice the cost of a
* similar forward seek.
*/
if (s1 >= last)
d1 = s1 - last;
else if (s1 + back_max >= last)
d1 = (last - s1) * bfqd->bfq_back_penalty;
else
wrap |= BFQ_RQ1_WRAP;
if (s2 >= last)
d2 = s2 - last;
else if (s2 + back_max >= last)
d2 = (last - s2) * bfqd->bfq_back_penalty;
else
wrap |= BFQ_RQ2_WRAP;
/* Found required data */
/*
* By doing switch() on the bit mask "wrap" we avoid having to
* check two variables for all permutations: --> faster!
*/
switch (wrap) {
case 0: /* common case for CFQ: rq1 and rq2 not wrapped */
if (d1 < d2)
return rq1;
else if (d2 < d1)
return rq2;
if (s1 >= s2)
return rq1;
else
return rq2;
case BFQ_RQ2_WRAP:
return rq1;
case BFQ_RQ1_WRAP:
return rq2;
case BFQ_RQ1_WRAP|BFQ_RQ2_WRAP: /* both rqs wrapped */
default:
/*
* Since both rqs are wrapped,
* start with the one that's further behind head
* (--> only *one* back seek required),
* since back seek takes more time than forward.
*/
if (s1 <= s2)
return rq1;
else
return rq2;
}
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
static struct bfq_queue *
bfq_rq_pos_tree_lookup(struct bfq_data *bfqd, struct rb_root *root,
sector_t sector, struct rb_node **ret_parent,
struct rb_node ***rb_link)
{
struct rb_node **p, *parent;
struct bfq_queue *bfqq = NULL;
parent = NULL;
p = &root->rb_node;
while (*p) {
struct rb_node **n;
parent = *p;
bfqq = rb_entry(parent, struct bfq_queue, pos_node);
/*
* Sort strictly based on sector. Smallest to the left,
* largest to the right.
*/
if (sector > blk_rq_pos(bfqq->next_rq))
n = &(*p)->rb_right;
else if (sector < blk_rq_pos(bfqq->next_rq))
n = &(*p)->rb_left;
else
break;
p = n;
bfqq = NULL;
}
*ret_parent = parent;
if (rb_link)
*rb_link = p;
bfq_log(bfqd, "rq_pos_tree_lookup %llu: returning %d",
(unsigned long long)sector,
bfqq ? bfqq->pid : 0);
return bfqq;
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_pos_tree_add_move(struct bfq_data *bfqd, struct bfq_queue *bfqq)
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
{
struct rb_node **p, *parent;
struct bfq_queue *__bfqq;
if (bfqq->pos_root) {
rb_erase(&bfqq->pos_node, bfqq->pos_root);
bfqq->pos_root = NULL;
}
if (bfq_class_idle(bfqq))
return;
if (!bfqq->next_rq)
return;
bfqq->pos_root = &bfq_bfqq_to_bfqg(bfqq)->rq_pos_tree;
__bfqq = bfq_rq_pos_tree_lookup(bfqd, bfqq->pos_root,
blk_rq_pos(bfqq->next_rq), &parent, &p);
if (!__bfqq) {
rb_link_node(&bfqq->pos_node, parent, p);
rb_insert_color(&bfqq->pos_node, bfqq->pos_root);
} else
bfqq->pos_root = NULL;
}
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
/*
* Tell whether there are active queues or groups with differentiated weights.
*/
static bool bfq_differentiated_weights(struct bfq_data *bfqd)
{
/*
* For weights to differ, at least one of the trees must contain
* at least two nodes.
*/
return (!RB_EMPTY_ROOT(&bfqd->queue_weights_tree) &&
(bfqd->queue_weights_tree.rb_node->rb_left ||
bfqd->queue_weights_tree.rb_node->rb_right)
#ifdef CONFIG_BFQ_GROUP_IOSCHED
) ||
(!RB_EMPTY_ROOT(&bfqd->group_weights_tree) &&
(bfqd->group_weights_tree.rb_node->rb_left ||
bfqd->group_weights_tree.rb_node->rb_right)
#endif
);
}
/*
* The following function returns true if every queue must receive the
* same share of the throughput (this condition is used when deciding
* whether idling may be disabled, see the comments in the function
* bfq_bfqq_may_idle()).
*
* Such a scenario occurs when:
* 1) all active queues have the same weight,
* 2) all active groups at the same level in the groups tree have the same
* weight,
* 3) all active groups at the same level in the groups tree have the same
* number of children.
*
* Unfortunately, keeping the necessary state for evaluating exactly the
* above symmetry conditions would be quite complex and time-consuming.
* Therefore this function evaluates, instead, the following stronger
* sub-conditions, for which it is much easier to maintain the needed
* state:
* 1) all active queues have the same weight,
* 2) all active groups have the same weight,
* 3) all active groups have at most one active child each.
* In particular, the last two conditions are always true if hierarchical
* support and the cgroups interface are not enabled, thus no state needs
* to be maintained in this case.
*/
static bool bfq_symmetric_scenario(struct bfq_data *bfqd)
{
return !bfq_differentiated_weights(bfqd);
}
/*
* If the weight-counter tree passed as input contains no counter for
* the weight of the input entity, then add that counter; otherwise just
* increment the existing counter.
*
* Note that weight-counter trees contain few nodes in mostly symmetric
* scenarios. For example, if all queues have the same weight, then the
* weight-counter tree for the queues may contain at most one node.
* This holds even if low_latency is on, because weight-raised queues
* are not inserted in the tree.
* In most scenarios, the rate at which nodes are created/destroyed
* should be low too.
*/
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_weights_tree_add(struct bfq_data *bfqd, struct bfq_entity *entity,
struct rb_root *root)
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
{
struct rb_node **new = &(root->rb_node), *parent = NULL;
/*
* Do not insert if the entity is already associated with a
* counter, which happens if:
* 1) the entity is associated with a queue,
* 2) a request arrival has caused the queue to become both
* non-weight-raised, and hence change its weight, and
* backlogged; in this respect, each of the two events
* causes an invocation of this function,
* 3) this is the invocation of this function caused by the
* second event. This second invocation is actually useless,
* and we handle this fact by exiting immediately. More
* efficient or clearer solutions might possibly be adopted.
*/
if (entity->weight_counter)
return;
while (*new) {
struct bfq_weight_counter *__counter = container_of(*new,
struct bfq_weight_counter,
weights_node);
parent = *new;
if (entity->weight == __counter->weight) {
entity->weight_counter = __counter;
goto inc_counter;
}
if (entity->weight < __counter->weight)
new = &((*new)->rb_left);
else
new = &((*new)->rb_right);
}
entity->weight_counter = kzalloc(sizeof(struct bfq_weight_counter),
GFP_ATOMIC);
/*
* In the unlucky event of an allocation failure, we just
* exit. This will cause the weight of entity to not be
* considered in bfq_differentiated_weights, which, in its
* turn, causes the scenario to be deemed wrongly symmetric in
* case entity's weight would have been the only weight making
* the scenario asymmetric. On the bright side, no unbalance
* will however occur when entity becomes inactive again (the
* invocation of this function is triggered by an activation
* of entity). In fact, bfq_weights_tree_remove does nothing
* if !entity->weight_counter.
*/
if (unlikely(!entity->weight_counter))
return;
entity->weight_counter->weight = entity->weight;
rb_link_node(&entity->weight_counter->weights_node, parent, new);
rb_insert_color(&entity->weight_counter->weights_node, root);
inc_counter:
entity->weight_counter->num_active++;
}
/*
* Decrement the weight counter associated with the entity, and, if the
* counter reaches 0, remove the counter from the tree.
* See the comments to the function bfq_weights_tree_add() for considerations
* about overhead.
*/
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_weights_tree_remove(struct bfq_data *bfqd, struct bfq_entity *entity,
struct rb_root *root)
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
{
if (!entity->weight_counter)
return;
entity->weight_counter->num_active--;
if (entity->weight_counter->num_active > 0)
goto reset_entity_pointer;
rb_erase(&entity->weight_counter->weights_node, root);
kfree(entity->weight_counter);
reset_entity_pointer:
entity->weight_counter = NULL;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Return expired entry, or NULL to just start from scratch in rbtree.
*/
static struct request *bfq_check_fifo(struct bfq_queue *bfqq,
struct request *last)
{
struct request *rq;
if (bfq_bfqq_fifo_expire(bfqq))
return NULL;
bfq_mark_bfqq_fifo_expire(bfqq);
rq = rq_entry_fifo(bfqq->fifo.next);
if (rq == last || ktime_get_ns() < rq->fifo_time)
return NULL;
bfq_log_bfqq(bfqq->bfqd, bfqq, "check_fifo: returned %p", rq);
return rq;
}
static struct request *bfq_find_next_rq(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
struct request *last)
{
struct rb_node *rbnext = rb_next(&last->rb_node);
struct rb_node *rbprev = rb_prev(&last->rb_node);
struct request *next, *prev = NULL;
/* Follow expired path, else get first next available. */
next = bfq_check_fifo(bfqq, last);
if (next)
return next;
if (rbprev)
prev = rb_entry_rq(rbprev);
if (rbnext)
next = rb_entry_rq(rbnext);
else {
rbnext = rb_first(&bfqq->sort_list);
if (rbnext && rbnext != &last->rb_node)
next = rb_entry_rq(rbnext);
}
return bfq_choose_req(bfqd, next, prev, blk_rq_pos(last));
}
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
/* see the definition of bfq_async_charge_factor for details */
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static unsigned long bfq_serv_to_charge(struct request *rq,
struct bfq_queue *bfqq)
{
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfq_bfqq_sync(bfqq) || bfqq->wr_coeff > 1)
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
return blk_rq_sectors(rq);
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
/*
* If there are no weight-raised queues, then amplify service
* by just the async charge factor; otherwise amplify service
* by twice the async charge factor, to further reduce latency
* for weight-raised queues.
*/
if (bfqq->bfqd->wr_busy_queues == 0)
return blk_rq_sectors(rq) * bfq_async_charge_factor;
return blk_rq_sectors(rq) * 2 * bfq_async_charge_factor;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
/**
* bfq_updated_next_req - update the queue after a new next_rq selection.
* @bfqd: the device data the queue belongs to.
* @bfqq: the queue to update.
*
* If the first request of a queue changes we make sure that the queue
* has enough budget to serve at least its first request (if the
* request has grown). We do this because if the queue has not enough
* budget for its first request, it has to go through two dispatch
* rounds to actually get it dispatched.
*/
static void bfq_updated_next_req(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
struct bfq_entity *entity = &bfqq->entity;
struct request *next_rq = bfqq->next_rq;
unsigned long new_budget;
if (!next_rq)
return;
if (bfqq == bfqd->in_service_queue)
/*
* In order not to break guarantees, budgets cannot be
* changed after an entity has been selected.
*/
return;
new_budget = max_t(unsigned long, bfqq->max_budget,
bfq_serv_to_charge(next_rq, bfqq));
if (entity->budget != new_budget) {
entity->budget = new_budget;
bfq_log_bfqq(bfqd, bfqq, "updated next rq: new budget %lu",
new_budget);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_requeue_bfqq(bfqd, bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
static void
bfq_bfqq_resume_state(struct bfq_queue *bfqq, struct bfq_io_cq *bic)
{
if (bic->saved_idle_window)
bfq_mark_bfqq_idle_window(bfqq);
else
bfq_clear_bfqq_idle_window(bfqq);
if (bic->saved_IO_bound)
bfq_mark_bfqq_IO_bound(bfqq);
else
bfq_clear_bfqq_IO_bound(bfqq);
bfqq->ttime = bic->saved_ttime;
bfqq->wr_coeff = bic->saved_wr_coeff;
bfqq->wr_start_at_switch_to_srt = bic->saved_wr_start_at_switch_to_srt;
bfqq->last_wr_start_finish = bic->saved_last_wr_start_finish;
bfqq->wr_cur_max_time = bic->saved_wr_cur_max_time;
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
if (bfqq->wr_coeff > 1 && (bfq_bfqq_in_large_burst(bfqq) ||
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
time_is_before_jiffies(bfqq->last_wr_start_finish +
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bfqq->wr_cur_max_time))) {
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfq_log_bfqq(bfqq->bfqd, bfqq,
"resume state: switching off wr");
bfqq->wr_coeff = 1;
}
/* make sure weight will be updated, however we got here */
bfqq->entity.prio_changed = 1;
}
static int bfqq_process_refs(struct bfq_queue *bfqq)
{
return bfqq->ref - bfqq->allocated - bfqq->entity.on_st;
}
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
/* Empty burst list and add just bfqq (see comments on bfq_handle_burst) */
static void bfq_reset_burst_list(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
struct bfq_queue *item;
struct hlist_node *n;
hlist_for_each_entry_safe(item, n, &bfqd->burst_list, burst_list_node)
hlist_del_init(&item->burst_list_node);
hlist_add_head(&bfqq->burst_list_node, &bfqd->burst_list);
bfqd->burst_size = 1;
bfqd->burst_parent_entity = bfqq->entity.parent;
}
/* Add bfqq to the list of queues in current burst (see bfq_handle_burst) */
static void bfq_add_to_burst(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
/* Increment burst size to take into account also bfqq */
bfqd->burst_size++;
if (bfqd->burst_size == bfqd->bfq_large_burst_thresh) {
struct bfq_queue *pos, *bfqq_item;
struct hlist_node *n;
/*
* Enough queues have been activated shortly after each
* other to consider this burst as large.
*/
bfqd->large_burst = true;
/*
* We can now mark all queues in the burst list as
* belonging to a large burst.
*/
hlist_for_each_entry(bfqq_item, &bfqd->burst_list,
burst_list_node)
bfq_mark_bfqq_in_large_burst(bfqq_item);
bfq_mark_bfqq_in_large_burst(bfqq);
/*
* From now on, and until the current burst finishes, any
* new queue being activated shortly after the last queue
* was inserted in the burst can be immediately marked as
* belonging to a large burst. So the burst list is not
* needed any more. Remove it.
*/
hlist_for_each_entry_safe(pos, n, &bfqd->burst_list,
burst_list_node)
hlist_del_init(&pos->burst_list_node);
} else /*
* Burst not yet large: add bfqq to the burst list. Do
* not increment the ref counter for bfqq, because bfqq
* is removed from the burst list before freeing bfqq
* in put_queue.
*/
hlist_add_head(&bfqq->burst_list_node, &bfqd->burst_list);
}
/*
* If many queues belonging to the same group happen to be created
* shortly after each other, then the processes associated with these
* queues have typically a common goal. In particular, bursts of queue
* creations are usually caused by services or applications that spawn
* many parallel threads/processes. Examples are systemd during boot,
* or git grep. To help these processes get their job done as soon as
* possible, it is usually better to not grant either weight-raising
* or device idling to their queues.
*
* In this comment we describe, firstly, the reasons why this fact
* holds, and, secondly, the next function, which implements the main
* steps needed to properly mark these queues so that they can then be
* treated in a different way.
*
* The above services or applications benefit mostly from a high
* throughput: the quicker the requests of the activated queues are
* cumulatively served, the sooner the target job of these queues gets
* completed. As a consequence, weight-raising any of these queues,
* which also implies idling the device for it, is almost always
* counterproductive. In most cases it just lowers throughput.
*
* On the other hand, a burst of queue creations may be caused also by
* the start of an application that does not consist of a lot of
* parallel I/O-bound threads. In fact, with a complex application,
* several short processes may need to be executed to start-up the
* application. In this respect, to start an application as quickly as
* possible, the best thing to do is in any case to privilege the I/O
* related to the application with respect to all other
* I/O. Therefore, the best strategy to start as quickly as possible
* an application that causes a burst of queue creations is to
* weight-raise all the queues created during the burst. This is the
* exact opposite of the best strategy for the other type of bursts.
*
* In the end, to take the best action for each of the two cases, the
* two types of bursts need to be distinguished. Fortunately, this
* seems relatively easy, by looking at the sizes of the bursts. In
* particular, we found a threshold such that only bursts with a
* larger size than that threshold are apparently caused by
* services or commands such as systemd or git grep. For brevity,
* hereafter we call just 'large' these bursts. BFQ *does not*
* weight-raise queues whose creation occurs in a large burst. In
* addition, for each of these queues BFQ performs or does not perform
* idling depending on which choice boosts the throughput more. The
* exact choice depends on the device and request pattern at
* hand.
*
* Unfortunately, false positives may occur while an interactive task
* is starting (e.g., an application is being started). The
* consequence is that the queues associated with the task do not
* enjoy weight raising as expected. Fortunately these false positives
* are very rare. They typically occur if some service happens to
* start doing I/O exactly when the interactive task starts.
*
* Turning back to the next function, it implements all the steps
* needed to detect the occurrence of a large burst and to properly
* mark all the queues belonging to it (so that they can then be
* treated in a different way). This goal is achieved by maintaining a
* "burst list" that holds, temporarily, the queues that belong to the
* burst in progress. The list is then used to mark these queues as
* belonging to a large burst if the burst does become large. The main
* steps are the following.
*
* . when the very first queue is created, the queue is inserted into the
* list (as it could be the first queue in a possible burst)
*
* . if the current burst has not yet become large, and a queue Q that does
* not yet belong to the burst is activated shortly after the last time
* at which a new queue entered the burst list, then the function appends
* Q to the burst list
*
* . if, as a consequence of the previous step, the burst size reaches
* the large-burst threshold, then
*
* . all the queues in the burst list are marked as belonging to a
* large burst
*
* . the burst list is deleted; in fact, the burst list already served
* its purpose (keeping temporarily track of the queues in a burst,
* so as to be able to mark them as belonging to a large burst in the
* previous sub-step), and now is not needed any more
*
* . the device enters a large-burst mode
*
* . if a queue Q that does not belong to the burst is created while
* the device is in large-burst mode and shortly after the last time
* at which a queue either entered the burst list or was marked as
* belonging to the current large burst, then Q is immediately marked
* as belonging to a large burst.
*
* . if a queue Q that does not belong to the burst is created a while
* later, i.e., not shortly after, than the last time at which a queue
* either entered the burst list or was marked as belonging to the
* current large burst, then the current burst is deemed as finished and:
*
* . the large-burst mode is reset if set
*
* . the burst list is emptied
*
* . Q is inserted in the burst list, as Q may be the first queue
* in a possible new burst (then the burst list contains just Q
* after this step).
*/
static void bfq_handle_burst(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
/*
* If bfqq is already in the burst list or is part of a large
* burst, or finally has just been split, then there is
* nothing else to do.
*/
if (!hlist_unhashed(&bfqq->burst_list_node) ||
bfq_bfqq_in_large_burst(bfqq) ||
time_is_after_eq_jiffies(bfqq->split_time +
msecs_to_jiffies(10)))
return;
/*
* If bfqq's creation happens late enough, or bfqq belongs to
* a different group than the burst group, then the current
* burst is finished, and related data structures must be
* reset.
*
* In this respect, consider the special case where bfqq is
* the very first queue created after BFQ is selected for this
* device. In this case, last_ins_in_burst and
* burst_parent_entity are not yet significant when we get
* here. But it is easy to verify that, whether or not the
* following condition is true, bfqq will end up being
* inserted into the burst list. In particular the list will
* happen to contain only bfqq. And this is exactly what has
* to happen, as bfqq may be the first queue of the first
* burst.
*/
if (time_is_before_jiffies(bfqd->last_ins_in_burst +
bfqd->bfq_burst_interval) ||
bfqq->entity.parent != bfqd->burst_parent_entity) {
bfqd->large_burst = false;
bfq_reset_burst_list(bfqd, bfqq);
goto end;
}
/*
* If we get here, then bfqq is being activated shortly after the
* last queue. So, if the current burst is also large, we can mark
* bfqq as belonging to this large burst immediately.
*/
if (bfqd->large_burst) {
bfq_mark_bfqq_in_large_burst(bfqq);
goto end;
}
/*
* If we get here, then a large-burst state has not yet been
* reached, but bfqq is being activated shortly after the last
* queue. Then we add bfqq to the burst.
*/
bfq_add_to_burst(bfqd, bfqq);
end:
/*
* At this point, bfqq either has been added to the current
* burst or has caused the current burst to terminate and a
* possible new burst to start. In particular, in the second
* case, bfqq has become the first queue in the possible new
* burst. In both cases last_ins_in_burst needs to be moved
* forward.
*/
bfqd->last_ins_in_burst = jiffies;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static int bfq_bfqq_budget_left(struct bfq_queue *bfqq)
{
struct bfq_entity *entity = &bfqq->entity;
return entity->budget - entity->service;
}
/*
* If enough samples have been computed, return the current max budget
* stored in bfqd, which is dynamically updated according to the
* estimated disk peak rate; otherwise return the default max budget
*/
static int bfq_max_budget(struct bfq_data *bfqd)
{
if (bfqd->budgets_assigned < bfq_stats_min_budgets)
return bfq_default_max_budget;
else
return bfqd->bfq_max_budget;
}
/*
* Return min budget, which is a fraction of the current or default
* max budget (trying with 1/32)
*/
static int bfq_min_budget(struct bfq_data *bfqd)
{
if (bfqd->budgets_assigned < bfq_stats_min_budgets)
return bfq_default_max_budget / 32;
else
return bfqd->bfq_max_budget / 32;
}
/*
* The next function, invoked after the input queue bfqq switches from
* idle to busy, updates the budget of bfqq. The function also tells
* whether the in-service queue should be expired, by returning
* true. The purpose of expiring the in-service queue is to give bfqq
* the chance to possibly preempt the in-service queue, and the reason
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* for preempting the in-service queue is to achieve one of the two
* goals below.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* 1. Guarantee to bfqq its reserved bandwidth even if bfqq has
* expired because it has remained idle. In particular, bfqq may have
* expired for one of the following two reasons:
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*
* - BFQQE_NO_MORE_REQUESTS bfqq did not enjoy any device idling
* and did not make it to issue a new request before its last
* request was served;
*
* - BFQQE_TOO_IDLE bfqq did enjoy device idling, but did not issue
* a new request before the expiration of the idling-time.
*
* Even if bfqq has expired for one of the above reasons, the process
* associated with the queue may be however issuing requests greedily,
* and thus be sensitive to the bandwidth it receives (bfqq may have
* remained idle for other reasons: CPU high load, bfqq not enjoying
* idling, I/O throttling somewhere in the path from the process to
* the I/O scheduler, ...). But if, after every expiration for one of
* the above two reasons, bfqq has to wait for the service of at least
* one full budget of another queue before being served again, then
* bfqq is likely to get a much lower bandwidth or resource time than
* its reserved ones. To address this issue, two countermeasures need
* to be taken.
*
* First, the budget and the timestamps of bfqq need to be updated in
* a special way on bfqq reactivation: they need to be updated as if
* bfqq did not remain idle and did not expire. In fact, if they are
* computed as if bfqq expired and remained idle until reactivation,
* then the process associated with bfqq is treated as if, instead of
* being greedy, it stopped issuing requests when bfqq remained idle,
* and restarts issuing requests only on this reactivation. In other
* words, the scheduler does not help the process recover the "service
* hole" between bfqq expiration and reactivation. As a consequence,
* the process receives a lower bandwidth than its reserved one. In
* contrast, to recover this hole, the budget must be updated as if
* bfqq was not expired at all before this reactivation, i.e., it must
* be set to the value of the remaining budget when bfqq was
* expired. Along the same line, timestamps need to be assigned the
* value they had the last time bfqq was selected for service, i.e.,
* before last expiration. Thus timestamps need to be back-shifted
* with respect to their normal computation (see [1] for more details
* on this tricky aspect).
*
* Secondly, to allow the process to recover the hole, the in-service
* queue must be expired too, to give bfqq the chance to preempt it
* immediately. In fact, if bfqq has to wait for a full budget of the
* in-service queue to be completed, then it may become impossible to
* let the process recover the hole, even if the back-shifted
* timestamps of bfqq are lower than those of the in-service queue. If
* this happens for most or all of the holes, then the process may not
* receive its reserved bandwidth. In this respect, it is worth noting
* that, being the service of outstanding requests unpreemptible, a
* little fraction of the holes may however be unrecoverable, thereby
* causing a little loss of bandwidth.
*
* The last important point is detecting whether bfqq does need this
* bandwidth recovery. In this respect, the next function deems the
* process associated with bfqq greedy, and thus allows it to recover
* the hole, if: 1) the process is waiting for the arrival of a new
* request (which implies that bfqq expired for one of the above two
* reasons), and 2) such a request has arrived soon. The first
* condition is controlled through the flag non_blocking_wait_rq,
* while the second through the flag arrived_in_time. If both
* conditions hold, then the function computes the budget in the
* above-described special way, and signals that the in-service queue
* should be expired. Timestamp back-shifting is done later in
* __bfq_activate_entity.
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*
* 2. Reduce latency. Even if timestamps are not backshifted to let
* the process associated with bfqq recover a service hole, bfqq may
* however happen to have, after being (re)activated, a lower finish
* timestamp than the in-service queue. That is, the next budget of
* bfqq may have to be completed before the one of the in-service
* queue. If this is the case, then preempting the in-service queue
* allows this goal to be achieved, apart from the unpreemptible,
* outstanding requests mentioned above.
*
* Unfortunately, regardless of which of the above two goals one wants
* to achieve, service trees need first to be updated to know whether
* the in-service queue must be preempted. To have service trees
* correctly updated, the in-service queue must be expired and
* rescheduled, and bfqq must be scheduled too. This is one of the
* most costly operations (in future versions, the scheduling
* mechanism may be re-designed in such a way to make it possible to
* know whether preemption is needed without needing to update service
* trees). In addition, queue preemptions almost always cause random
* I/O, and thus loss of throughput. Because of these facts, the next
* function adopts the following simple scheme to avoid both costly
* operations and too frequent preemptions: it requests the expiration
* of the in-service queue (unconditionally) only for queues that need
* to recover a hole, or that either are weight-raised or deserve to
* be weight-raised.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
static bool bfq_bfqq_update_budg_for_activation(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bool arrived_in_time,
bool wr_or_deserves_wr)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
struct bfq_entity *entity = &bfqq->entity;
if (bfq_bfqq_non_blocking_wait_rq(bfqq) && arrived_in_time) {
/*
* We do not clear the flag non_blocking_wait_rq here, as
* the latter is used in bfq_activate_bfqq to signal
* that timestamps need to be back-shifted (and is
* cleared right after).
*/
/*
* In next assignment we rely on that either
* entity->service or entity->budget are not updated
* on expiration if bfqq is empty (see
* __bfq_bfqq_recalc_budget). Thus both quantities
* remain unchanged after such an expiration, and the
* following statement therefore assigns to
* entity->budget the remaining budget on such an
* expiration. For clarity, entity->service is not
* updated on expiration in any case, and, in normal
* operation, is reset only when bfqq is selected for
* service (see bfq_get_next_queue).
*/
entity->budget = min_t(unsigned long,
bfq_bfqq_budget_left(bfqq),
bfqq->max_budget);
return true;
}
entity->budget = max_t(unsigned long, bfqq->max_budget,
bfq_serv_to_charge(bfqq->next_rq, bfqq));
bfq_clear_bfqq_non_blocking_wait_rq(bfqq);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
return wr_or_deserves_wr;
}
static unsigned int bfq_wr_duration(struct bfq_data *bfqd)
{
u64 dur;
if (bfqd->bfq_wr_max_time > 0)
return bfqd->bfq_wr_max_time;
dur = bfqd->RT_prod;
do_div(dur, bfqd->peak_rate);
/*
* Limit duration between 3 and 13 seconds. Tests show that
* higher values than 13 seconds often yield the opposite of
* the desired result, i.e., worsen responsiveness by letting
* non-interactive and non-soft-real-time applications
* preserve weight raising for a too long time interval.
*
* On the other end, lower values than 3 seconds make it
* difficult for most interactive tasks to complete their jobs
* before weight-raising finishes.
*/
if (dur > msecs_to_jiffies(13000))
dur = msecs_to_jiffies(13000);
else if (dur < msecs_to_jiffies(3000))
dur = msecs_to_jiffies(3000);
return dur;
}
static void bfq_update_bfqq_wr_on_rq_arrival(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
unsigned int old_wr_coeff,
bool wr_or_deserves_wr,
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bool interactive,
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bool in_burst,
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bool soft_rt)
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
{
if (old_wr_coeff == 1 && wr_or_deserves_wr) {
/* start a weight-raising period */
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
if (interactive) {
bfqq->wr_coeff = bfqd->bfq_wr_coeff;
bfqq->wr_cur_max_time = bfq_wr_duration(bfqd);
} else {
bfqq->wr_start_at_switch_to_srt = jiffies;
bfqq->wr_coeff = bfqd->bfq_wr_coeff *
BFQ_SOFTRT_WEIGHT_FACTOR;
bfqq->wr_cur_max_time =
bfqd->bfq_wr_rt_max_time;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* If needed, further reduce budget to make sure it is
* close to bfqq's backlog, so as to reduce the
* scheduling-error component due to a too large
* budget. Do not care about throughput consequences,
* but only about latency. Finally, do not assign a
* too small budget either, to avoid increasing
* latency by causing too frequent expirations.
*/
bfqq->entity.budget = min_t(unsigned long,
bfqq->entity.budget,
2 * bfq_min_budget(bfqd));
} else if (old_wr_coeff > 1) {
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
if (interactive) { /* update wr coeff and duration */
bfqq->wr_coeff = bfqd->bfq_wr_coeff;
bfqq->wr_cur_max_time = bfq_wr_duration(bfqd);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
} else if (in_burst)
bfqq->wr_coeff = 1;
else if (soft_rt) {
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
/*
* The application is now or still meeting the
* requirements for being deemed soft rt. We
* can then correctly and safely (re)charge
* the weight-raising duration for the
* application with the weight-raising
* duration for soft rt applications.
*
* In particular, doing this recharge now, i.e.,
* before the weight-raising period for the
* application finishes, reduces the probability
* of the following negative scenario:
* 1) the weight of a soft rt application is
* raised at startup (as for any newly
* created application),
* 2) since the application is not interactive,
* at a certain time weight-raising is
* stopped for the application,
* 3) at that time the application happens to
* still have pending requests, and hence
* is destined to not have a chance to be
* deemed soft rt before these requests are
* completed (see the comments to the
* function bfq_bfqq_softrt_next_start()
* for details on soft rt detection),
* 4) these pending requests experience a high
* latency because the application is not
* weight-raised while they are pending.
*/
if (bfqq->wr_cur_max_time !=
bfqd->bfq_wr_rt_max_time) {
bfqq->wr_start_at_switch_to_srt =
bfqq->last_wr_start_finish;
bfqq->wr_cur_max_time =
bfqd->bfq_wr_rt_max_time;
bfqq->wr_coeff = bfqd->bfq_wr_coeff *
BFQ_SOFTRT_WEIGHT_FACTOR;
}
bfqq->last_wr_start_finish = jiffies;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
}
static bool bfq_bfqq_idle_for_long_time(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
return bfqq->dispatched == 0 &&
time_is_before_jiffies(
bfqq->budget_timeout +
bfqd->bfq_wr_min_idle_time);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static void bfq_bfqq_handle_idle_busy_switch(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
int old_wr_coeff,
struct request *rq,
bool *interactive)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bool soft_rt, in_burst, wr_or_deserves_wr,
bfqq_wants_to_preempt,
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
idle_for_long_time = bfq_bfqq_idle_for_long_time(bfqd, bfqq),
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* See the comments on
* bfq_bfqq_update_budg_for_activation for
* details on the usage of the next variable.
*/
arrived_in_time = ktime_get_ns() <=
bfqq->ttime.last_end_request +
bfqd->bfq_slice_idle * 3;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_update_io_add(bfqq_group(RQ_BFQQ(rq)), bfqq, rq->cmd_flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* bfqq deserves to be weight-raised if:
* - it is sync,
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
* - it does not belong to a large burst,
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
* - it has been idle for enough time or is soft real-time,
* - is linked to a bfq_io_cq (it is not shared in any sense).
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*/
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
in_burst = bfq_bfqq_in_large_burst(bfqq);
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
soft_rt = bfqd->bfq_wr_max_softrt_rate > 0 &&
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
!in_burst &&
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
time_is_before_jiffies(bfqq->soft_rt_next_start);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
*interactive = !in_burst && idle_for_long_time;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
wr_or_deserves_wr = bfqd->low_latency &&
(bfqq->wr_coeff > 1 ||
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
(bfq_bfqq_sync(bfqq) &&
bfqq->bic && (*interactive || soft_rt)));
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Using the last flag, update budget and check whether bfqq
* may want to preempt the in-service queue.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
bfqq_wants_to_preempt =
bfq_bfqq_update_budg_for_activation(bfqd, bfqq,
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
arrived_in_time,
wr_or_deserves_wr);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
/*
* If bfqq happened to be activated in a burst, but has been
* idle for much more than an interactive queue, then we
* assume that, in the overall I/O initiated in the burst, the
* I/O associated with bfqq is finished. So bfqq does not need
* to be treated as a queue belonging to a burst
* anymore. Accordingly, we reset bfqq's in_large_burst flag
* if set, and remove bfqq from the burst list if it's
* there. We do not decrement burst_size, because the fact
* that bfqq does not need to belong to the burst list any
* more does not invalidate the fact that bfqq was created in
* a burst.
*/
if (likely(!bfq_bfqq_just_created(bfqq)) &&
idle_for_long_time &&
time_is_before_jiffies(
bfqq->budget_timeout +
msecs_to_jiffies(10000))) {
hlist_del_init(&bfqq->burst_list_node);
bfq_clear_bfqq_in_large_burst(bfqq);
}
bfq_clear_bfqq_just_created(bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (!bfq_bfqq_IO_bound(bfqq)) {
if (arrived_in_time) {
bfqq->requests_within_timer++;
if (bfqq->requests_within_timer >=
bfqd->bfq_requests_within_timer)
bfq_mark_bfqq_IO_bound(bfqq);
} else
bfqq->requests_within_timer = 0;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqd->low_latency) {
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
if (unlikely(time_is_after_jiffies(bfqq->split_time)))
/* wraparound */
bfqq->split_time =
jiffies - bfqd->bfq_wr_min_idle_time - 1;
if (time_is_before_jiffies(bfqq->split_time +
bfqd->bfq_wr_min_idle_time)) {
bfq_update_bfqq_wr_on_rq_arrival(bfqd, bfqq,
old_wr_coeff,
wr_or_deserves_wr,
*interactive,
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
in_burst,
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
soft_rt);
if (old_wr_coeff != bfqq->wr_coeff)
bfqq->entity.prio_changed = 1;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqq->last_idle_bklogged = jiffies;
bfqq->service_from_backlogged = 0;
bfq_clear_bfqq_softrt_update(bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_add_bfqq_busy(bfqd, bfqq);
/*
* Expire in-service queue only if preemption may be needed
* for guarantees. In this respect, the function
* next_queue_may_preempt just checks a simple, necessary
* condition, and not a sufficient condition based on
* timestamps. In fact, for the latter condition to be
* evaluated, timestamps would need first to be updated, and
* this operation is quite costly (see the comments on the
* function bfq_bfqq_update_budg_for_activation).
*/
if (bfqd->in_service_queue && bfqq_wants_to_preempt &&
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqd->in_service_queue->wr_coeff < bfqq->wr_coeff &&
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
next_queue_may_preempt(bfqd))
bfq_bfqq_expire(bfqd, bfqd->in_service_queue,
false, BFQQE_PREEMPTED);
}
static void bfq_add_request(struct request *rq)
{
struct bfq_queue *bfqq = RQ_BFQQ(rq);
struct bfq_data *bfqd = bfqq->bfqd;
struct request *next_rq, *prev;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
unsigned int old_wr_coeff = bfqq->wr_coeff;
bool interactive = false;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq, "add_request %d", rq_is_sync(rq));
bfqq->queued[rq_is_sync(rq)]++;
bfqd->queued++;
elv_rb_add(&bfqq->sort_list, rq);
/*
* Check if this request is a better next-serve candidate.
*/
prev = bfqq->next_rq;
next_rq = bfq_choose_req(bfqd, bfqq->next_rq, rq, bfqd->last_position);
bfqq->next_rq = next_rq;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* Adjust priority tree position, if next_rq changes.
*/
if (prev != bfqq->next_rq)
bfq_pos_tree_add_move(bfqd, bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (!bfq_bfqq_busy(bfqq)) /* switching to busy ... */
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfq_bfqq_handle_idle_busy_switch(bfqd, bfqq, old_wr_coeff,
rq, &interactive);
else {
if (bfqd->low_latency && old_wr_coeff == 1 && !rq_is_sync(rq) &&
time_is_before_jiffies(
bfqq->last_wr_start_finish +
bfqd->bfq_wr_min_inter_arr_async)) {
bfqq->wr_coeff = bfqd->bfq_wr_coeff;
bfqq->wr_cur_max_time = bfq_wr_duration(bfqd);
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
bfqd->wr_busy_queues++;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqq->entity.prio_changed = 1;
}
if (prev != bfqq->next_rq)
bfq_updated_next_req(bfqd, bfqq);
}
/*
* Assign jiffies to last_wr_start_finish in the following
* cases:
*
* . if bfqq is not going to be weight-raised, because, for
* non weight-raised queues, last_wr_start_finish stores the
* arrival time of the last request; as of now, this piece
* of information is used only for deciding whether to
* weight-raise async queues
*
* . if bfqq is not weight-raised, because, if bfqq is now
* switching to weight-raised, then last_wr_start_finish
* stores the time when weight-raising starts
*
* . if bfqq is interactive, because, regardless of whether
* bfqq is currently weight-raised, the weight-raising
* period must start or restart (this case is considered
* separately because it is not detected by the above
* conditions, if bfqq is already weight-raised)
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
*
* last_wr_start_finish has to be updated also if bfqq is soft
* real-time, because the weight-raising period is constantly
* restarted on idle-to-busy transitions for these queues, but
* this is already done in bfq_bfqq_handle_idle_busy_switch if
* needed.
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*/
if (bfqd->low_latency &&
(old_wr_coeff == 1 || bfqq->wr_coeff == 1 || interactive))
bfqq->last_wr_start_finish = jiffies;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static struct request *bfq_find_rq_fmerge(struct bfq_data *bfqd,
struct bio *bio,
struct request_queue *q)
{
struct bfq_queue *bfqq = bfqd->bio_bfqq;
if (bfqq)
return elv_rb_find(&bfqq->sort_list, bio_end_sector(bio));
return NULL;
}
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
static sector_t get_sdist(sector_t last_pos, struct request *rq)
{
if (last_pos)
return abs(blk_rq_pos(rq) - last_pos);
return 0;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
#if 0 /* Still not clear if we can do without next two functions */
static void bfq_activate_request(struct request_queue *q, struct request *rq)
{
struct bfq_data *bfqd = q->elevator->elevator_data;
bfqd->rq_in_driver++;
}
static void bfq_deactivate_request(struct request_queue *q, struct request *rq)
{
struct bfq_data *bfqd = q->elevator->elevator_data;
bfqd->rq_in_driver--;
}
#endif
static void bfq_remove_request(struct request_queue *q,
struct request *rq)
{
struct bfq_queue *bfqq = RQ_BFQQ(rq);
struct bfq_data *bfqd = bfqq->bfqd;
const int sync = rq_is_sync(rq);
if (bfqq->next_rq == rq) {
bfqq->next_rq = bfq_find_next_rq(bfqd, bfqq, rq);
bfq_updated_next_req(bfqd, bfqq);
}
if (rq->queuelist.prev != &rq->queuelist)
list_del_init(&rq->queuelist);
bfqq->queued[sync]--;
bfqd->queued--;
elv_rb_del(&bfqq->sort_list, rq);
elv_rqhash_del(q, rq);
if (q->last_merge == rq)
q->last_merge = NULL;
if (RB_EMPTY_ROOT(&bfqq->sort_list)) {
bfqq->next_rq = NULL;
if (bfq_bfqq_busy(bfqq) && bfqq != bfqd->in_service_queue) {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_del_bfqq_busy(bfqd, bfqq, false);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* bfqq emptied. In normal operation, when
* bfqq is empty, bfqq->entity.service and
* bfqq->entity.budget must contain,
* respectively, the service received and the
* budget used last time bfqq emptied. These
* facts do not hold in this case, as at least
* this last removal occurred while bfqq is
* not in service. To avoid inconsistencies,
* reset both bfqq->entity.service and
* bfqq->entity.budget, if bfqq has still a
* process that may issue I/O requests to it.
*/
bfqq->entity.budget = bfqq->entity.service = 0;
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* Remove queue from request-position tree as it is empty.
*/
if (bfqq->pos_root) {
rb_erase(&bfqq->pos_node, bfqq->pos_root);
bfqq->pos_root = NULL;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
if (rq->cmd_flags & REQ_META)
bfqq->meta_pending--;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_update_io_remove(bfqq_group(bfqq), rq->cmd_flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static bool bfq_bio_merge(struct blk_mq_hw_ctx *hctx, struct bio *bio)
{
struct request_queue *q = hctx->queue;
struct bfq_data *bfqd = q->elevator->elevator_data;
struct request *free = NULL;
/*
* bfq_bic_lookup grabs the queue_lock: invoke it now and
* store its return value for later use, to avoid nesting
* queue_lock inside the bfqd->lock. We assume that the bic
* returned by bfq_bic_lookup does not go away before
* bfqd->lock is taken.
*/
struct bfq_io_cq *bic = bfq_bic_lookup(bfqd, current->io_context, q);
bool ret;
spin_lock_irq(&bfqd->lock);
if (bic)
bfqd->bio_bfqq = bic_to_bfqq(bic, op_is_sync(bio->bi_opf));
else
bfqd->bio_bfqq = NULL;
bfqd->bio_bic = bic;
ret = blk_mq_sched_try_merge(q, bio, &free);
if (free)
blk_mq_free_request(free);
spin_unlock_irq(&bfqd->lock);
return ret;
}
static int bfq_request_merge(struct request_queue *q, struct request **req,
struct bio *bio)
{
struct bfq_data *bfqd = q->elevator->elevator_data;
struct request *__rq;
__rq = bfq_find_rq_fmerge(bfqd, bio, q);
if (__rq && elv_bio_merge_ok(__rq, bio)) {
*req = __rq;
return ELEVATOR_FRONT_MERGE;
}
return ELEVATOR_NO_MERGE;
}
static void bfq_request_merged(struct request_queue *q, struct request *req,
enum elv_merge type)
{
if (type == ELEVATOR_FRONT_MERGE &&
rb_prev(&req->rb_node) &&
blk_rq_pos(req) <
blk_rq_pos(container_of(rb_prev(&req->rb_node),
struct request, rb_node))) {
struct bfq_queue *bfqq = RQ_BFQQ(req);
struct bfq_data *bfqd = bfqq->bfqd;
struct request *prev, *next_rq;
/* Reposition request in its sort_list */
elv_rb_del(&bfqq->sort_list, req);
elv_rb_add(&bfqq->sort_list, req);
/* Choose next request to be served for bfqq */
prev = bfqq->next_rq;
next_rq = bfq_choose_req(bfqd, bfqq->next_rq, req,
bfqd->last_position);
bfqq->next_rq = next_rq;
/*
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
* If next_rq changes, update both the queue's budget to
* fit the new request and the queue's position in its
* rq_pos_tree.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
if (prev != bfqq->next_rq) {
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_updated_next_req(bfqd, bfqq);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfq_pos_tree_add_move(bfqd, bfqq);
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
}
static void bfq_requests_merged(struct request_queue *q, struct request *rq,
struct request *next)
{
struct bfq_queue *bfqq = RQ_BFQQ(rq), *next_bfqq = RQ_BFQQ(next);
if (!RB_EMPTY_NODE(&rq->rb_node))
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
goto end;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
spin_lock_irq(&bfqq->bfqd->lock);
/*
* If next and rq belong to the same bfq_queue and next is older
* than rq, then reposition rq in the fifo (by substituting next
* with rq). Otherwise, if next and rq belong to different
* bfq_queues, never reposition rq: in fact, we would have to
* reposition it with respect to next's position in its own fifo,
* which would most certainly be too expensive with respect to
* the benefits.
*/
if (bfqq == next_bfqq &&
!list_empty(&rq->queuelist) && !list_empty(&next->queuelist) &&
next->fifo_time < rq->fifo_time) {
list_del_init(&rq->queuelist);
list_replace_init(&next->queuelist, &rq->queuelist);
rq->fifo_time = next->fifo_time;
}
if (bfqq->next_rq == next)
bfqq->next_rq = rq;
bfq_remove_request(q, next);
spin_unlock_irq(&bfqq->bfqd->lock);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
end:
bfqg_stats_update_io_merged(bfqq_group(bfqq), next->cmd_flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/* Must be called with bfqq != NULL */
static void bfq_bfqq_end_wr(struct bfq_queue *bfqq)
{
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
if (bfq_bfqq_busy(bfqq))
bfqq->bfqd->wr_busy_queues--;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqq->wr_coeff = 1;
bfqq->wr_cur_max_time = 0;
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqq->last_wr_start_finish = jiffies;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Trigger a weight change on the next invocation of
* __bfq_entity_update_weight_prio.
*/
bfqq->entity.prio_changed = 1;
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_end_wr_async_queues(struct bfq_data *bfqd,
struct bfq_group *bfqg)
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
{
int i, j;
for (i = 0; i < 2; i++)
for (j = 0; j < IOPRIO_BE_NR; j++)
if (bfqg->async_bfqq[i][j])
bfq_bfqq_end_wr(bfqg->async_bfqq[i][j]);
if (bfqg->async_idle_bfqq)
bfq_bfqq_end_wr(bfqg->async_idle_bfqq);
}
static void bfq_end_wr(struct bfq_data *bfqd)
{
struct bfq_queue *bfqq;
spin_lock_irq(&bfqd->lock);
list_for_each_entry(bfqq, &bfqd->active_list, bfqq_list)
bfq_bfqq_end_wr(bfqq);
list_for_each_entry(bfqq, &bfqd->idle_list, bfqq_list)
bfq_bfqq_end_wr(bfqq);
bfq_end_wr_async(bfqd);
spin_unlock_irq(&bfqd->lock);
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
static sector_t bfq_io_struct_pos(void *io_struct, bool request)
{
if (request)
return blk_rq_pos(io_struct);
else
return ((struct bio *)io_struct)->bi_iter.bi_sector;
}
static int bfq_rq_close_to_sector(void *io_struct, bool request,
sector_t sector)
{
return abs(bfq_io_struct_pos(io_struct, request) - sector) <=
BFQQ_CLOSE_THR;
}
static struct bfq_queue *bfqq_find_close(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
sector_t sector)
{
struct rb_root *root = &bfq_bfqq_to_bfqg(bfqq)->rq_pos_tree;
struct rb_node *parent, *node;
struct bfq_queue *__bfqq;
if (RB_EMPTY_ROOT(root))
return NULL;
/*
* First, if we find a request starting at the end of the last
* request, choose it.
*/
__bfqq = bfq_rq_pos_tree_lookup(bfqd, root, sector, &parent, NULL);
if (__bfqq)
return __bfqq;
/*
* If the exact sector wasn't found, the parent of the NULL leaf
* will contain the closest sector (rq_pos_tree sorted by
* next_request position).
*/
__bfqq = rb_entry(parent, struct bfq_queue, pos_node);
if (bfq_rq_close_to_sector(__bfqq->next_rq, true, sector))
return __bfqq;
if (blk_rq_pos(__bfqq->next_rq) < sector)
node = rb_next(&__bfqq->pos_node);
else
node = rb_prev(&__bfqq->pos_node);
if (!node)
return NULL;
__bfqq = rb_entry(node, struct bfq_queue, pos_node);
if (bfq_rq_close_to_sector(__bfqq->next_rq, true, sector))
return __bfqq;
return NULL;
}
static struct bfq_queue *bfq_find_close_cooperator(struct bfq_data *bfqd,
struct bfq_queue *cur_bfqq,
sector_t sector)
{
struct bfq_queue *bfqq;
/*
* We shall notice if some of the queues are cooperating,
* e.g., working closely on the same area of the device. In
* that case, we can group them together and: 1) don't waste
* time idling, and 2) serve the union of their requests in
* the best possible order for throughput.
*/
bfqq = bfqq_find_close(bfqd, cur_bfqq, sector);
if (!bfqq || bfqq == cur_bfqq)
return NULL;
return bfqq;
}
static struct bfq_queue *
bfq_setup_merge(struct bfq_queue *bfqq, struct bfq_queue *new_bfqq)
{
int process_refs, new_process_refs;
struct bfq_queue *__bfqq;
/*
* If there are no process references on the new_bfqq, then it is
* unsafe to follow the ->new_bfqq chain as other bfqq's in the chain
* may have dropped their last reference (not just their last process
* reference).
*/
if (!bfqq_process_refs(new_bfqq))
return NULL;
/* Avoid a circular list and skip interim queue merges. */
while ((__bfqq = new_bfqq->new_bfqq)) {
if (__bfqq == bfqq)
return NULL;
new_bfqq = __bfqq;
}
process_refs = bfqq_process_refs(bfqq);
new_process_refs = bfqq_process_refs(new_bfqq);
/*
* If the process for the bfqq has gone away, there is no
* sense in merging the queues.
*/
if (process_refs == 0 || new_process_refs == 0)
return NULL;
bfq_log_bfqq(bfqq->bfqd, bfqq, "scheduling merge with queue %d",
new_bfqq->pid);
/*
* Merging is just a redirection: the requests of the process
* owning one of the two queues are redirected to the other queue.
* The latter queue, in its turn, is set as shared if this is the
* first time that the requests of some process are redirected to
* it.
*
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
* We redirect bfqq to new_bfqq and not the opposite, because
* we are in the context of the process owning bfqq, thus we
* have the io_cq of this process. So we can immediately
* configure this io_cq to redirect the requests of the
* process to new_bfqq. In contrast, the io_cq of new_bfqq is
* not available any more (new_bfqq->bic == NULL).
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
*
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
* Anyway, even in case new_bfqq coincides with the in-service
* queue, redirecting requests the in-service queue is the
* best option, as we feed the in-service queue with new
* requests close to the last request served and, by doing so,
* are likely to increase the throughput.
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
*/
bfqq->new_bfqq = new_bfqq;
new_bfqq->ref += process_refs;
return new_bfqq;
}
static bool bfq_may_be_close_cooperator(struct bfq_queue *bfqq,
struct bfq_queue *new_bfqq)
{
if (bfq_class_idle(bfqq) || bfq_class_idle(new_bfqq) ||
(bfqq->ioprio_class != new_bfqq->ioprio_class))
return false;
/*
* If either of the queues has already been detected as seeky,
* then merging it with the other queue is unlikely to lead to
* sequential I/O.
*/
if (BFQQ_SEEKY(bfqq) || BFQQ_SEEKY(new_bfqq))
return false;
/*
* Interleaved I/O is known to be done by (some) applications
* only for reads, so it does not make sense to merge async
* queues.
*/
if (!bfq_bfqq_sync(bfqq) || !bfq_bfqq_sync(new_bfqq))
return false;
return true;
}
/*
* If this function returns true, then bfqq cannot be merged. The idea
* is that true cooperation happens very early after processes start
* to do I/O. Usually, late cooperations are just accidental false
* positives. In case bfqq is weight-raised, such false positives
* would evidently degrade latency guarantees for bfqq.
*/
static bool wr_from_too_long(struct bfq_queue *bfqq)
{
return bfqq->wr_coeff > 1 &&
time_is_before_jiffies(bfqq->last_wr_start_finish +
msecs_to_jiffies(100));
}
/*
* Attempt to schedule a merge of bfqq with the currently in-service
* queue or with a close queue among the scheduled queues. Return
* NULL if no merge was scheduled, a pointer to the shared bfq_queue
* structure otherwise.
*
* The OOM queue is not allowed to participate to cooperation: in fact, since
* the requests temporarily redirected to the OOM queue could be redirected
* again to dedicated queues at any time, the state needed to correctly
* handle merging with the OOM queue would be quite complex and expensive
* to maintain. Besides, in such a critical condition as an out of memory,
* the benefits of queue merging may be little relevant, or even negligible.
*
* Weight-raised queues can be merged only if their weight-raising
* period has just started. In fact cooperating processes are usually
* started together. Thus, with this filter we avoid false positives
* that would jeopardize low-latency guarantees.
*
* WARNING: queue merging may impair fairness among non-weight raised
* queues, for at least two reasons: 1) the original weight of a
* merged queue may change during the merged state, 2) even being the
* weight the same, a merged queue may be bloated with many more
* requests than the ones produced by its originally-associated
* process.
*/
static struct bfq_queue *
bfq_setup_cooperator(struct bfq_data *bfqd, struct bfq_queue *bfqq,
void *io_struct, bool request)
{
struct bfq_queue *in_service_bfqq, *new_bfqq;
if (bfqq->new_bfqq)
return bfqq->new_bfqq;
if (!io_struct ||
wr_from_too_long(bfqq) ||
unlikely(bfqq == &bfqd->oom_bfqq))
return NULL;
/* If there is only one backlogged queue, don't search. */
if (bfqd->busy_queues == 1)
return NULL;
in_service_bfqq = bfqd->in_service_queue;
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
if (!in_service_bfqq || in_service_bfqq == bfqq
|| wr_from_too_long(in_service_bfqq) ||
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
unlikely(in_service_bfqq == &bfqd->oom_bfqq))
goto check_scheduled;
if (bfq_rq_close_to_sector(io_struct, request, bfqd->last_position) &&
bfqq->entity.parent == in_service_bfqq->entity.parent &&
bfq_may_be_close_cooperator(bfqq, in_service_bfqq)) {
new_bfqq = bfq_setup_merge(bfqq, in_service_bfqq);
if (new_bfqq)
return new_bfqq;
}
/*
* Check whether there is a cooperator among currently scheduled
* queues. The only thing we need is that the bio/request is not
* NULL, as we need it to establish whether a cooperator exists.
*/
check_scheduled:
new_bfqq = bfq_find_close_cooperator(bfqd, bfqq,
bfq_io_struct_pos(io_struct, request));
if (new_bfqq && !wr_from_too_long(new_bfqq) &&
likely(new_bfqq != &bfqd->oom_bfqq) &&
bfq_may_be_close_cooperator(bfqq, new_bfqq))
return bfq_setup_merge(bfqq, new_bfqq);
return NULL;
}
static void bfq_bfqq_save_state(struct bfq_queue *bfqq)
{
struct bfq_io_cq *bic = bfqq->bic;
/*
* If !bfqq->bic, the queue is already shared or its requests
* have already been redirected to a shared queue; both idle window
* and weight raising state have already been saved. Do nothing.
*/
if (!bic)
return;
bic->saved_ttime = bfqq->ttime;
bic->saved_idle_window = bfq_bfqq_idle_window(bfqq);
bic->saved_IO_bound = bfq_bfqq_IO_bound(bfqq);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bic->saved_in_large_burst = bfq_bfqq_in_large_burst(bfqq);
bic->was_in_burst_list = !hlist_unhashed(&bfqq->burst_list_node);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bic->saved_wr_coeff = bfqq->wr_coeff;
bic->saved_wr_start_at_switch_to_srt = bfqq->wr_start_at_switch_to_srt;
bic->saved_last_wr_start_finish = bfqq->last_wr_start_finish;
bic->saved_wr_cur_max_time = bfqq->wr_cur_max_time;
}
static void
bfq_merge_bfqqs(struct bfq_data *bfqd, struct bfq_io_cq *bic,
struct bfq_queue *bfqq, struct bfq_queue *new_bfqq)
{
bfq_log_bfqq(bfqd, bfqq, "merging with queue %lu",
(unsigned long)new_bfqq->pid);
/* Save weight raising and idle window of the merged queues */
bfq_bfqq_save_state(bfqq);
bfq_bfqq_save_state(new_bfqq);
if (bfq_bfqq_IO_bound(bfqq))
bfq_mark_bfqq_IO_bound(new_bfqq);
bfq_clear_bfqq_IO_bound(bfqq);
/*
* If bfqq is weight-raised, then let new_bfqq inherit
* weight-raising. To reduce false positives, neglect the case
* where bfqq has just been created, but has not yet made it
* to be weight-raised (which may happen because EQM may merge
* bfqq even before bfq_add_request is executed for the first
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
* time for bfqq). Handling this case would however be very
* easy, thanks to the flag just_created.
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
*/
if (new_bfqq->wr_coeff == 1 && bfqq->wr_coeff > 1) {
new_bfqq->wr_coeff = bfqq->wr_coeff;
new_bfqq->wr_cur_max_time = bfqq->wr_cur_max_time;
new_bfqq->last_wr_start_finish = bfqq->last_wr_start_finish;
new_bfqq->wr_start_at_switch_to_srt =
bfqq->wr_start_at_switch_to_srt;
if (bfq_bfqq_busy(new_bfqq))
bfqd->wr_busy_queues++;
new_bfqq->entity.prio_changed = 1;
}
if (bfqq->wr_coeff > 1) { /* bfqq has given its wr to new_bfqq */
bfqq->wr_coeff = 1;
bfqq->entity.prio_changed = 1;
if (bfq_bfqq_busy(bfqq))
bfqd->wr_busy_queues--;
}
bfq_log_bfqq(bfqd, new_bfqq, "merge_bfqqs: wr_busy %d",
bfqd->wr_busy_queues);
/*
* Merge queues (that is, let bic redirect its requests to new_bfqq)
*/
bic_set_bfqq(bic, new_bfqq, 1);
bfq_mark_bfqq_coop(new_bfqq);
/*
* new_bfqq now belongs to at least two bics (it is a shared queue):
* set new_bfqq->bic to NULL. bfqq either:
* - does not belong to any bic any more, and hence bfqq->bic must
* be set to NULL, or
* - is a queue whose owning bics have already been redirected to a
* different queue, hence the queue is destined to not belong to
* any bic soon and bfqq->bic is already NULL (therefore the next
* assignment causes no harm).
*/
new_bfqq->bic = NULL;
bfqq->bic = NULL;
/* release process reference to bfqq */
bfq_put_queue(bfqq);
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static bool bfq_allow_bio_merge(struct request_queue *q, struct request *rq,
struct bio *bio)
{
struct bfq_data *bfqd = q->elevator->elevator_data;
bool is_sync = op_is_sync(bio->bi_opf);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
struct bfq_queue *bfqq = bfqd->bio_bfqq, *new_bfqq;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Disallow merge of a sync bio into an async request.
*/
if (is_sync && !rq_is_sync(rq))
return false;
/*
* Lookup the bfqq that this bio will be queued with. Allow
* merge only if rq is queued there.
*/
if (!bfqq)
return false;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* We take advantage of this function to perform an early merge
* of the queues of possible cooperating processes.
*/
new_bfqq = bfq_setup_cooperator(bfqd, bfqq, bio, false);
if (new_bfqq) {
/*
* bic still points to bfqq, then it has not yet been
* redirected to some other bfq_queue, and a queue
* merge beween bfqq and new_bfqq can be safely
* fulfillled, i.e., bic can be redirected to new_bfqq
* and bfqq can be put.
*/
bfq_merge_bfqqs(bfqd, bfqd->bio_bic, bfqq,
new_bfqq);
/*
* If we get here, bio will be queued into new_queue,
* so use new_bfqq to decide whether bio and rq can be
* merged.
*/
bfqq = new_bfqq;
/*
* Change also bqfd->bio_bfqq, as
* bfqd->bio_bic now points to new_bfqq, and
* this function may be invoked again (and then may
* use again bqfd->bio_bfqq).
*/
bfqd->bio_bfqq = bfqq;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return bfqq == RQ_BFQQ(rq);
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Set the maximum time for the in-service queue to consume its
* budget. This prevents seeky processes from lowering the throughput.
* In practice, a time-slice service scheme is used with seeky
* processes.
*/
static void bfq_set_budget_timeout(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
unsigned int timeout_coeff;
if (bfqq->wr_cur_max_time == bfqd->bfq_wr_rt_max_time)
timeout_coeff = 1;
else
timeout_coeff = bfqq->entity.weight / bfqq->entity.orig_weight;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqd->last_budget_start = ktime_get();
bfqq->budget_timeout = jiffies +
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqd->bfq_timeout * timeout_coeff;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static void __bfq_set_in_service_queue(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
if (bfqq) {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_update_avg_queue_size(bfqq_group(bfqq));
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_clear_bfqq_fifo_expire(bfqq);
bfqd->budgets_assigned = (bfqd->budgets_assigned * 7 + 256) / 8;
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
if (time_is_before_jiffies(bfqq->last_wr_start_finish) &&
bfqq->wr_coeff > 1 &&
bfqq->wr_cur_max_time == bfqd->bfq_wr_rt_max_time &&
time_is_before_jiffies(bfqq->budget_timeout)) {
/*
* For soft real-time queues, move the start
* of the weight-raising period forward by the
* time the queue has not received any
* service. Otherwise, a relatively long
* service delay is likely to cause the
* weight-raising period of the queue to end,
* because of the short duration of the
* weight-raising period of a soft real-time
* queue. It is worth noting that this move
* is not so dangerous for the other queues,
* because soft real-time queues are not
* greedy.
*
* To not add a further variable, we use the
* overloaded field budget_timeout to
* determine for how long the queue has not
* received service, i.e., how much time has
* elapsed since the queue expired. However,
* this is a little imprecise, because
* budget_timeout is set to jiffies if bfqq
* not only expires, but also remains with no
* request.
*/
if (time_after(bfqq->budget_timeout,
bfqq->last_wr_start_finish))
bfqq->last_wr_start_finish +=
jiffies - bfqq->budget_timeout;
else
bfqq->last_wr_start_finish = jiffies;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfq_set_budget_timeout(bfqd, bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq,
"set_in_service_queue, cur-budget = %d",
bfqq->entity.budget);
}
bfqd->in_service_queue = bfqq;
}
/*
* Get and set a new queue for service.
*/
static struct bfq_queue *bfq_set_in_service_queue(struct bfq_data *bfqd)
{
struct bfq_queue *bfqq = bfq_get_next_queue(bfqd);
__bfq_set_in_service_queue(bfqd, bfqq);
return bfqq;
}
static void bfq_arm_slice_timer(struct bfq_data *bfqd)
{
struct bfq_queue *bfqq = bfqd->in_service_queue;
u32 sl;
bfq_mark_bfqq_wait_request(bfqq);
/*
* We don't want to idle for seeks, but we do want to allow
* fair distribution of slice time for a process doing back-to-back
* seeks. So allow a little bit of time for him to submit a new rq.
*/
sl = bfqd->bfq_slice_idle;
/*
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
* Unless the queue is being weight-raised or the scenario is
* asymmetric, grant only minimum idle time if the queue
* is seeky. A long idling is preserved for a weight-raised
* queue, or, more in general, in an asymmetric scenario,
* because a long idling is needed for guaranteeing to a queue
* its reserved share of the throughput (in particular, it is
* needed if the queue has a higher weight than some other
* queue).
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
if (BFQQ_SEEKY(bfqq) && bfqq->wr_coeff == 1 &&
bfq_symmetric_scenario(bfqd))
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
sl = min_t(u64, sl, BFQ_MIN_TT);
bfqd->last_idling_start = ktime_get();
hrtimer_start(&bfqd->idle_slice_timer, ns_to_ktime(sl),
HRTIMER_MODE_REL);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_set_start_idle_time(bfqq_group(bfqq));
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
/*
* In autotuning mode, max_budget is dynamically recomputed as the
* amount of sectors transferred in timeout at the estimated peak
* rate. This enables BFQ to utilize a full timeslice with a full
* budget, even if the in-service queue is served at peak rate. And
* this maximises throughput with sequential workloads.
*/
static unsigned long bfq_calc_max_budget(struct bfq_data *bfqd)
{
return (u64)bfqd->peak_rate * USEC_PER_MSEC *
jiffies_to_msecs(bfqd->bfq_timeout)>>BFQ_RATE_SHIFT;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Update parameters related to throughput and responsiveness, as a
* function of the estimated peak rate. See comments on
* bfq_calc_max_budget(), and on T_slow and T_fast arrays.
*/
static void update_thr_responsiveness_params(struct bfq_data *bfqd)
{
int dev_type = blk_queue_nonrot(bfqd->queue);
if (bfqd->bfq_user_max_budget == 0)
bfqd->bfq_max_budget =
bfq_calc_max_budget(bfqd);
if (bfqd->device_speed == BFQ_BFQD_FAST &&
bfqd->peak_rate < device_speed_thresh[dev_type]) {
bfqd->device_speed = BFQ_BFQD_SLOW;
bfqd->RT_prod = R_slow[dev_type] *
T_slow[dev_type];
} else if (bfqd->device_speed == BFQ_BFQD_SLOW &&
bfqd->peak_rate > device_speed_thresh[dev_type]) {
bfqd->device_speed = BFQ_BFQD_FAST;
bfqd->RT_prod = R_fast[dev_type] *
T_fast[dev_type];
}
bfq_log(bfqd,
"dev_type %s dev_speed_class = %s (%llu sects/sec), thresh %llu setcs/sec",
dev_type == 0 ? "ROT" : "NONROT",
bfqd->device_speed == BFQ_BFQD_FAST ? "FAST" : "SLOW",
bfqd->device_speed == BFQ_BFQD_FAST ?
(USEC_PER_SEC*(u64)R_fast[dev_type])>>BFQ_RATE_SHIFT :
(USEC_PER_SEC*(u64)R_slow[dev_type])>>BFQ_RATE_SHIFT,
(USEC_PER_SEC*(u64)device_speed_thresh[dev_type])>>
BFQ_RATE_SHIFT);
}
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
static void bfq_reset_rate_computation(struct bfq_data *bfqd,
struct request *rq)
{
if (rq != NULL) { /* new rq dispatch now, reset accordingly */
bfqd->last_dispatch = bfqd->first_dispatch = ktime_get_ns();
bfqd->peak_rate_samples = 1;
bfqd->sequential_samples = 0;
bfqd->tot_sectors_dispatched = bfqd->last_rq_max_size =
blk_rq_sectors(rq);
} else /* no new rq dispatched, just reset the number of samples */
bfqd->peak_rate_samples = 0; /* full re-init on next disp. */
bfq_log(bfqd,
"reset_rate_computation at end, sample %u/%u tot_sects %llu",
bfqd->peak_rate_samples, bfqd->sequential_samples,
bfqd->tot_sectors_dispatched);
}
static void bfq_update_rate_reset(struct bfq_data *bfqd, struct request *rq)
{
u32 rate, weight, divisor;
/*
* For the convergence property to hold (see comments on
* bfq_update_peak_rate()) and for the assessment to be
* reliable, a minimum number of samples must be present, and
* a minimum amount of time must have elapsed. If not so, do
* not compute new rate. Just reset parameters, to get ready
* for a new evaluation attempt.
*/
if (bfqd->peak_rate_samples < BFQ_RATE_MIN_SAMPLES ||
bfqd->delta_from_first < BFQ_RATE_MIN_INTERVAL)
goto reset_computation;
/*
* If a new request completion has occurred after last
* dispatch, then, to approximate the rate at which requests
* have been served by the device, it is more precise to
* extend the observation interval to the last completion.
*/
bfqd->delta_from_first =
max_t(u64, bfqd->delta_from_first,
bfqd->last_completion - bfqd->first_dispatch);
/*
* Rate computed in sects/usec, and not sects/nsec, for
* precision issues.
*/
rate = div64_ul(bfqd->tot_sectors_dispatched<<BFQ_RATE_SHIFT,
div_u64(bfqd->delta_from_first, NSEC_PER_USEC));
/*
* Peak rate not updated if:
* - the percentage of sequential dispatches is below 3/4 of the
* total, and rate is below the current estimated peak rate
* - rate is unreasonably high (> 20M sectors/sec)
*/
if ((bfqd->sequential_samples < (3 * bfqd->peak_rate_samples)>>2 &&
rate <= bfqd->peak_rate) ||
rate > 20<<BFQ_RATE_SHIFT)
goto reset_computation;
/*
* We have to update the peak rate, at last! To this purpose,
* we use a low-pass filter. We compute the smoothing constant
* of the filter as a function of the 'weight' of the new
* measured rate.
*
* As can be seen in next formulas, we define this weight as a
* quantity proportional to how sequential the workload is,
* and to how long the observation time interval is.
*
* The weight runs from 0 to 8. The maximum value of the
* weight, 8, yields the minimum value for the smoothing
* constant. At this minimum value for the smoothing constant,
* the measured rate contributes for half of the next value of
* the estimated peak rate.
*
* So, the first step is to compute the weight as a function
* of how sequential the workload is. Note that the weight
* cannot reach 9, because bfqd->sequential_samples cannot
* become equal to bfqd->peak_rate_samples, which, in its
* turn, holds true because bfqd->sequential_samples is not
* incremented for the first sample.
*/
weight = (9 * bfqd->sequential_samples) / bfqd->peak_rate_samples;
/*
* Second step: further refine the weight as a function of the
* duration of the observation interval.
*/
weight = min_t(u32, 8,
div_u64(weight * bfqd->delta_from_first,
BFQ_RATE_REF_INTERVAL));
/*
* Divisor ranging from 10, for minimum weight, to 2, for
* maximum weight.
*/
divisor = 10 - weight;
/*
* Finally, update peak rate:
*
* peak_rate = peak_rate * (divisor-1) / divisor + rate / divisor
*/
bfqd->peak_rate *= divisor-1;
bfqd->peak_rate /= divisor;
rate /= divisor; /* smoothing constant alpha = 1/divisor */
bfqd->peak_rate += rate;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
update_thr_responsiveness_params(bfqd);
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
reset_computation:
bfq_reset_rate_computation(bfqd, rq);
}
/*
* Update the read/write peak rate (the main quantity used for
* auto-tuning, see update_thr_responsiveness_params()).
*
* It is not trivial to estimate the peak rate (correctly): because of
* the presence of sw and hw queues between the scheduler and the
* device components that finally serve I/O requests, it is hard to
* say exactly when a given dispatched request is served inside the
* device, and for how long. As a consequence, it is hard to know
* precisely at what rate a given set of requests is actually served
* by the device.
*
* On the opposite end, the dispatch time of any request is trivially
* available, and, from this piece of information, the "dispatch rate"
* of requests can be immediately computed. So, the idea in the next
* function is to use what is known, namely request dispatch times
* (plus, when useful, request completion times), to estimate what is
* unknown, namely in-device request service rate.
*
* The main issue is that, because of the above facts, the rate at
* which a certain set of requests is dispatched over a certain time
* interval can vary greatly with respect to the rate at which the
* same requests are then served. But, since the size of any
* intermediate queue is limited, and the service scheme is lossless
* (no request is silently dropped), the following obvious convergence
* property holds: the number of requests dispatched MUST become
* closer and closer to the number of requests completed as the
* observation interval grows. This is the key property used in
* the next function to estimate the peak service rate as a function
* of the observed dispatch rate. The function assumes to be invoked
* on every request dispatch.
*/
static void bfq_update_peak_rate(struct bfq_data *bfqd, struct request *rq)
{
u64 now_ns = ktime_get_ns();
if (bfqd->peak_rate_samples == 0) { /* first dispatch */
bfq_log(bfqd, "update_peak_rate: goto reset, samples %d",
bfqd->peak_rate_samples);
bfq_reset_rate_computation(bfqd, rq);
goto update_last_values; /* will add one sample */
}
/*
* Device idle for very long: the observation interval lasting
* up to this dispatch cannot be a valid observation interval
* for computing a new peak rate (similarly to the late-
* completion event in bfq_completed_request()). Go to
* update_rate_and_reset to have the following three steps
* taken:
* - close the observation interval at the last (previous)
* request dispatch or completion
* - compute rate, if possible, for that observation interval
* - start a new observation interval with this dispatch
*/
if (now_ns - bfqd->last_dispatch > 100*NSEC_PER_MSEC &&
bfqd->rq_in_driver == 0)
goto update_rate_and_reset;
/* Update sampling information */
bfqd->peak_rate_samples++;
if ((bfqd->rq_in_driver > 0 ||
now_ns - bfqd->last_completion < BFQ_MIN_TT)
&& get_sdist(bfqd->last_position, rq) < BFQQ_SEEK_THR)
bfqd->sequential_samples++;
bfqd->tot_sectors_dispatched += blk_rq_sectors(rq);
/* Reset max observed rq size every 32 dispatches */
if (likely(bfqd->peak_rate_samples % 32))
bfqd->last_rq_max_size =
max_t(u32, blk_rq_sectors(rq), bfqd->last_rq_max_size);
else
bfqd->last_rq_max_size = blk_rq_sectors(rq);
bfqd->delta_from_first = now_ns - bfqd->first_dispatch;
/* Target observation interval not yet reached, go on sampling */
if (bfqd->delta_from_first < BFQ_RATE_REF_INTERVAL)
goto update_last_values;
update_rate_and_reset:
bfq_update_rate_reset(bfqd, rq);
update_last_values:
bfqd->last_position = blk_rq_pos(rq) + blk_rq_sectors(rq);
bfqd->last_dispatch = now_ns;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Remove request from internal lists.
*/
static void bfq_dispatch_remove(struct request_queue *q, struct request *rq)
{
struct bfq_queue *bfqq = RQ_BFQQ(rq);
/*
* For consistency, the next instruction should have been
* executed after removing the request from the queue and
* dispatching it. We execute instead this instruction before
* bfq_remove_request() (and hence introduce a temporary
* inconsistency), for efficiency. In fact, should this
* dispatch occur for a non in-service bfqq, this anticipated
* increment prevents two counters related to bfqq->dispatched
* from risking to be, first, uselessly decremented, and then
* incremented again when the (new) value of bfqq->dispatched
* happens to be taken into account.
*/
bfqq->dispatched++;
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
bfq_update_peak_rate(q->elevator->elevator_data, rq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_remove_request(q, rq);
}
static void __bfq_bfqq_expire(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* If this bfqq is shared between multiple processes, check
* to make sure that those processes are still issuing I/Os
* within the mean seek distance. If not, it may be time to
* break the queues apart again.
*/
if (bfq_bfqq_coop(bfqq) && BFQQ_SEEKY(bfqq))
bfq_mark_bfqq_split_coop(bfqq);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (RB_EMPTY_ROOT(&bfqq->sort_list)) {
if (bfqq->dispatched == 0)
/*
* Overloading budget_timeout field to store
* the time at which the queue remains with no
* backlog and no outstanding request; used by
* the weight-raising mechanism.
*/
bfqq->budget_timeout = jiffies;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_del_bfqq_busy(bfqd, bfqq, true);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
} else {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_requeue_bfqq(bfqd, bfqq);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* Resort priority tree of potential close cooperators.
*/
bfq_pos_tree_add_move(bfqd, bfqq);
}
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
/*
* All in-service entities must have been properly deactivated
* or requeued before executing the next function, which
* resets all in-service entites as no more in service.
*/
__bfq_bfqd_reset_in_service(bfqd);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
/**
* __bfq_bfqq_recalc_budget - try to adapt the budget to the @bfqq behavior.
* @bfqd: device data.
* @bfqq: queue to update.
* @reason: reason for expiration.
*
* Handle the feedback on @bfqq budget at queue expiration.
* See the body for detailed comments.
*/
static void __bfq_bfqq_recalc_budget(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
enum bfqq_expiration reason)
{
struct request *next_rq;
int budget, min_budget;
min_budget = bfq_min_budget(bfqd);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqq->wr_coeff == 1)
budget = bfqq->max_budget;
else /*
* Use a constant, low budget for weight-raised queues,
* to help achieve a low latency. Keep it slightly higher
* than the minimum possible budget, to cause a little
* bit fewer expirations.
*/
budget = 2 * min_budget;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq, "recalc_budg: last budg %d, budg left %d",
bfqq->entity.budget, bfq_bfqq_budget_left(bfqq));
bfq_log_bfqq(bfqd, bfqq, "recalc_budg: last max_budg %d, min budg %d",
budget, bfq_min_budget(bfqd));
bfq_log_bfqq(bfqd, bfqq, "recalc_budg: sync %d, seeky %d",
bfq_bfqq_sync(bfqq), BFQQ_SEEKY(bfqd->in_service_queue));
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfq_bfqq_sync(bfqq) && bfqq->wr_coeff == 1) {
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
switch (reason) {
/*
* Caveat: in all the following cases we trade latency
* for throughput.
*/
case BFQQE_TOO_IDLE:
block, bfq: improve throughput boosting The feedback-loop algorithm used by BFQ to compute queue (process) budgets is basically a set of three update rules, one for each of the main reasons why a queue may be expired. If many processes suddenly switch from sporadic I/O to greedy and sequential I/O, then these rules are quite slow to assign large budgets to these processes, and hence to achieve a high throughput. On the opposite side, BFQ assigns the maximum possible budget B_max to a just-created queue. This allows a high throughput to be achieved immediately if the associated process is I/O-bound and performs sequential I/O from the beginning. But it also increases the worst-case latency experienced by the first requests issued by the process, because the larger the budget of a queue waiting for service is, the later the queue will be served by B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or soft real-time application. To tackle these throughput and latency problems, on one hand this patch changes the initial budget value to B_max/2. On the other hand, it re-tunes the three rules, adopting a more aggressive, multiplicative increase/linear decrease scheme. This scheme trades latency for throughput more than before, and tends to assign large budgets quickly to processes that are or become I/O-bound. For two of the expiration reasons, the new version of the rules also contains some more little improvements, briefly described below. *No more backlog.* In this case, the budget was larger than the number of sectors actually read/written by the process before it stopped doing I/O. Hence, to reduce latency for the possible future I/O requests of the process, the old rule simply set the next budget to the number of sectors actually consumed by the process. However, if there are still outstanding requests, then the process may have not yet issued its next request just because it is still waiting for the completion of some of the still outstanding ones. If this sub-case holds true, then the new rule, instead of decreasing the budget, doubles it, proactively, in the hope that: 1) a larger budget will fit the actual needs of the process, and 2) the process is sequential and hence a higher throughput will be achieved by serving the process longer after granting it access to the device. *Budget timeout*. The original rule set the new budget to the maximum value B_max, to maximize throughput and let all processes experiencing budget timeouts receive the same share of the device time. In our experiments we verified that this sudden jump to B_max did not provide sensible benefits; rather it increased the latency of processes performing sporadic and short I/O. The new rule only doubles the budget. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:09 +07:00
/*
* This is the only case where we may reduce
* the budget: if there is no request of the
* process still waiting for completion, then
* we assume (tentatively) that the timer has
* expired because the batch of requests of
* the process could have been served with a
* smaller budget. Hence, betting that
* process will behave in the same way when it
* becomes backlogged again, we reduce its
* next budget. As long as we guess right,
* this budget cut reduces the latency
* experienced by the process.
*
* However, if there are still outstanding
* requests, then the process may have not yet
* issued its next request just because it is
* still waiting for the completion of some of
* the still outstanding ones. So in this
* subcase we do not reduce its budget, on the
* contrary we increase it to possibly boost
* the throughput, as discussed in the
* comments to the BUDGET_TIMEOUT case.
*/
if (bfqq->dispatched > 0) /* still outstanding reqs */
budget = min(budget * 2, bfqd->bfq_max_budget);
else {
if (budget > 5 * min_budget)
budget -= 4 * min_budget;
else
budget = min_budget;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
break;
case BFQQE_BUDGET_TIMEOUT:
block, bfq: improve throughput boosting The feedback-loop algorithm used by BFQ to compute queue (process) budgets is basically a set of three update rules, one for each of the main reasons why a queue may be expired. If many processes suddenly switch from sporadic I/O to greedy and sequential I/O, then these rules are quite slow to assign large budgets to these processes, and hence to achieve a high throughput. On the opposite side, BFQ assigns the maximum possible budget B_max to a just-created queue. This allows a high throughput to be achieved immediately if the associated process is I/O-bound and performs sequential I/O from the beginning. But it also increases the worst-case latency experienced by the first requests issued by the process, because the larger the budget of a queue waiting for service is, the later the queue will be served by B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or soft real-time application. To tackle these throughput and latency problems, on one hand this patch changes the initial budget value to B_max/2. On the other hand, it re-tunes the three rules, adopting a more aggressive, multiplicative increase/linear decrease scheme. This scheme trades latency for throughput more than before, and tends to assign large budgets quickly to processes that are or become I/O-bound. For two of the expiration reasons, the new version of the rules also contains some more little improvements, briefly described below. *No more backlog.* In this case, the budget was larger than the number of sectors actually read/written by the process before it stopped doing I/O. Hence, to reduce latency for the possible future I/O requests of the process, the old rule simply set the next budget to the number of sectors actually consumed by the process. However, if there are still outstanding requests, then the process may have not yet issued its next request just because it is still waiting for the completion of some of the still outstanding ones. If this sub-case holds true, then the new rule, instead of decreasing the budget, doubles it, proactively, in the hope that: 1) a larger budget will fit the actual needs of the process, and 2) the process is sequential and hence a higher throughput will be achieved by serving the process longer after granting it access to the device. *Budget timeout*. The original rule set the new budget to the maximum value B_max, to maximize throughput and let all processes experiencing budget timeouts receive the same share of the device time. In our experiments we verified that this sudden jump to B_max did not provide sensible benefits; rather it increased the latency of processes performing sporadic and short I/O. The new rule only doubles the budget. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:09 +07:00
/*
* We double the budget here because it gives
* the chance to boost the throughput if this
* is not a seeky process (and has bumped into
* this timeout because of, e.g., ZBR).
*/
budget = min(budget * 2, bfqd->bfq_max_budget);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
break;
case BFQQE_BUDGET_EXHAUSTED:
/*
* The process still has backlog, and did not
* let either the budget timeout or the disk
* idling timeout expire. Hence it is not
* seeky, has a short thinktime and may be
* happy with a higher budget too. So
* definitely increase the budget of this good
* candidate to boost the disk throughput.
*/
block, bfq: improve throughput boosting The feedback-loop algorithm used by BFQ to compute queue (process) budgets is basically a set of three update rules, one for each of the main reasons why a queue may be expired. If many processes suddenly switch from sporadic I/O to greedy and sequential I/O, then these rules are quite slow to assign large budgets to these processes, and hence to achieve a high throughput. On the opposite side, BFQ assigns the maximum possible budget B_max to a just-created queue. This allows a high throughput to be achieved immediately if the associated process is I/O-bound and performs sequential I/O from the beginning. But it also increases the worst-case latency experienced by the first requests issued by the process, because the larger the budget of a queue waiting for service is, the later the queue will be served by B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or soft real-time application. To tackle these throughput and latency problems, on one hand this patch changes the initial budget value to B_max/2. On the other hand, it re-tunes the three rules, adopting a more aggressive, multiplicative increase/linear decrease scheme. This scheme trades latency for throughput more than before, and tends to assign large budgets quickly to processes that are or become I/O-bound. For two of the expiration reasons, the new version of the rules also contains some more little improvements, briefly described below. *No more backlog.* In this case, the budget was larger than the number of sectors actually read/written by the process before it stopped doing I/O. Hence, to reduce latency for the possible future I/O requests of the process, the old rule simply set the next budget to the number of sectors actually consumed by the process. However, if there are still outstanding requests, then the process may have not yet issued its next request just because it is still waiting for the completion of some of the still outstanding ones. If this sub-case holds true, then the new rule, instead of decreasing the budget, doubles it, proactively, in the hope that: 1) a larger budget will fit the actual needs of the process, and 2) the process is sequential and hence a higher throughput will be achieved by serving the process longer after granting it access to the device. *Budget timeout*. The original rule set the new budget to the maximum value B_max, to maximize throughput and let all processes experiencing budget timeouts receive the same share of the device time. In our experiments we verified that this sudden jump to B_max did not provide sensible benefits; rather it increased the latency of processes performing sporadic and short I/O. The new rule only doubles the budget. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:09 +07:00
budget = min(budget * 4, bfqd->bfq_max_budget);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
break;
case BFQQE_NO_MORE_REQUESTS:
/*
* For queues that expire for this reason, it
* is particularly important to keep the
* budget close to the actual service they
* need. Doing so reduces the timestamp
* misalignment problem described in the
* comments in the body of
* __bfq_activate_entity. In fact, suppose
* that a queue systematically expires for
* BFQQE_NO_MORE_REQUESTS and presents a
* new request in time to enjoy timestamp
* back-shifting. The larger the budget of the
* queue is with respect to the service the
* queue actually requests in each service
* slot, the more times the queue can be
* reactivated with the same virtual finish
* time. It follows that, even if this finish
* time is pushed to the system virtual time
* to reduce the consequent timestamp
* misalignment, the queue unjustly enjoys for
* many re-activations a lower finish time
* than all newly activated queues.
*
* The service needed by bfqq is measured
* quite precisely by bfqq->entity.service.
* Since bfqq does not enjoy device idling,
* bfqq->entity.service is equal to the number
* of sectors that the process associated with
* bfqq requested to read/write before waiting
* for request completions, or blocking for
* other reasons.
*/
budget = max_t(int, bfqq->entity.service, min_budget);
break;
default:
return;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
} else if (!bfq_bfqq_sync(bfqq)) {
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Async queues get always the maximum possible
* budget, as for them we do not care about latency
* (in addition, their ability to dispatch is limited
* by the charging factor).
*/
budget = bfqd->bfq_max_budget;
}
bfqq->max_budget = budget;
if (bfqd->budgets_assigned >= bfq_stats_min_budgets &&
!bfqd->bfq_user_max_budget)
bfqq->max_budget = min(bfqq->max_budget, bfqd->bfq_max_budget);
/*
* If there is still backlog, then assign a new budget, making
* sure that it is large enough for the next request. Since
* the finish time of bfqq must be kept in sync with the
* budget, be sure to call __bfq_bfqq_expire() *after* this
* update.
*
* If there is no backlog, then no need to update the budget;
* it will be updated on the arrival of a new request.
*/
next_rq = bfqq->next_rq;
if (next_rq)
bfqq->entity.budget = max_t(unsigned long, bfqq->max_budget,
bfq_serv_to_charge(next_rq, bfqq));
bfq_log_bfqq(bfqd, bfqq, "head sect: %u, new budget %d",
next_rq ? blk_rq_sectors(next_rq) : 0,
bfqq->entity.budget);
}
/*
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
* Return true if the process associated with bfqq is "slow". The slow
* flag is used, in addition to the budget timeout, to reduce the
* amount of service provided to seeky processes, and thus reduce
* their chances to lower the throughput. More details in the comments
* on the function bfq_bfqq_expire().
*
* An important observation is in order: as discussed in the comments
* on the function bfq_update_peak_rate(), with devices with internal
* queues, it is hard if ever possible to know when and for how long
* an I/O request is processed by the device (apart from the trivial
* I/O pattern where a new request is dispatched only after the
* previous one has been completed). This makes it hard to evaluate
* the real rate at which the I/O requests of each bfq_queue are
* served. In fact, for an I/O scheduler like BFQ, serving a
* bfq_queue means just dispatching its requests during its service
* slot (i.e., until the budget of the queue is exhausted, or the
* queue remains idle, or, finally, a timeout fires). But, during the
* service slot of a bfq_queue, around 100 ms at most, the device may
* be even still processing requests of bfq_queues served in previous
* service slots. On the opposite end, the requests of the in-service
* bfq_queue may be completed after the service slot of the queue
* finishes.
*
* Anyway, unless more sophisticated solutions are used
* (where possible), the sum of the sizes of the requests dispatched
* during the service slot of a bfq_queue is probably the only
* approximation available for the service received by the bfq_queue
* during its service slot. And this sum is the quantity used in this
* function to evaluate the I/O speed of a process.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
static bool bfq_bfqq_is_slow(struct bfq_data *bfqd, struct bfq_queue *bfqq,
bool compensate, enum bfqq_expiration reason,
unsigned long *delta_ms)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
ktime_t delta_ktime;
u32 delta_usecs;
bool slow = BFQQ_SEEKY(bfqq); /* if delta too short, use seekyness */
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
if (!bfq_bfqq_sync(bfqq))
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return false;
if (compensate)
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
delta_ktime = bfqd->last_idling_start;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
else
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
delta_ktime = ktime_get();
delta_ktime = ktime_sub(delta_ktime, bfqd->last_budget_start);
delta_usecs = ktime_to_us(delta_ktime);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/* don't use too short time intervals */
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
if (delta_usecs < 1000) {
if (blk_queue_nonrot(bfqd->queue))
/*
* give same worst-case guarantees as idling
* for seeky
*/
*delta_ms = BFQ_MIN_TT / NSEC_PER_MSEC;
else /* charge at least one seek */
*delta_ms = bfq_slice_idle / NSEC_PER_MSEC;
return slow;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
*delta_ms = delta_usecs / USEC_PER_MSEC;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
* Use only long (> 20ms) intervals to filter out excessive
* spikes in service rate estimation.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
if (delta_usecs > 20000) {
/*
* Caveat for rotational devices: processes doing I/O
* in the slower disk zones tend to be slow(er) even
* if not seeky. In this respect, the estimated peak
* rate is likely to be an average over the disk
* surface. Accordingly, to not be too harsh with
* unlucky processes, a process is deemed slow only if
* its rate has been lower than half of the estimated
* peak rate.
*/
slow = bfqq->entity.service < bfqd->bfq_max_budget / 2;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
bfq_log_bfqq(bfqd, bfqq, "bfq_bfqq_is_slow: slow %d", slow);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
return slow;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
/*
* To be deemed as soft real-time, an application must meet two
* requirements. First, the application must not require an average
* bandwidth higher than the approximate bandwidth required to playback or
* record a compressed high-definition video.
* The next function is invoked on the completion of the last request of a
* batch, to compute the next-start time instant, soft_rt_next_start, such
* that, if the next request of the application does not arrive before
* soft_rt_next_start, then the above requirement on the bandwidth is met.
*
* The second requirement is that the request pattern of the application is
* isochronous, i.e., that, after issuing a request or a batch of requests,
* the application stops issuing new requests until all its pending requests
* have been completed. After that, the application may issue a new batch,
* and so on.
* For this reason the next function is invoked to compute
* soft_rt_next_start only for applications that meet this requirement,
* whereas soft_rt_next_start is set to infinity for applications that do
* not.
*
* Unfortunately, even a greedy application may happen to behave in an
* isochronous way if the CPU load is high. In fact, the application may
* stop issuing requests while the CPUs are busy serving other processes,
* then restart, then stop again for a while, and so on. In addition, if
* the disk achieves a low enough throughput with the request pattern
* issued by the application (e.g., because the request pattern is random
* and/or the device is slow), then the application may meet the above
* bandwidth requirement too. To prevent such a greedy application to be
* deemed as soft real-time, a further rule is used in the computation of
* soft_rt_next_start: soft_rt_next_start must be higher than the current
* time plus the maximum time for which the arrival of a request is waited
* for when a sync queue becomes idle, namely bfqd->bfq_slice_idle.
* This filters out greedy applications, as the latter issue instead their
* next request as soon as possible after the last one has been completed
* (in contrast, when a batch of requests is completed, a soft real-time
* application spends some time processing data).
*
* Unfortunately, the last filter may easily generate false positives if
* only bfqd->bfq_slice_idle is used as a reference time interval and one
* or both the following cases occur:
* 1) HZ is so low that the duration of a jiffy is comparable to or higher
* than bfqd->bfq_slice_idle. This happens, e.g., on slow devices with
* HZ=100.
* 2) jiffies, instead of increasing at a constant rate, may stop increasing
* for a while, then suddenly 'jump' by several units to recover the lost
* increments. This seems to happen, e.g., inside virtual machines.
* To address this issue, we do not use as a reference time interval just
* bfqd->bfq_slice_idle, but bfqd->bfq_slice_idle plus a few jiffies. In
* particular we add the minimum number of jiffies for which the filter
* seems to be quite precise also in embedded systems and KVM/QEMU virtual
* machines.
*/
static unsigned long bfq_bfqq_softrt_next_start(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
return max(bfqq->last_idle_bklogged +
HZ * bfqq->service_from_backlogged /
bfqd->bfq_wr_max_softrt_rate,
jiffies + nsecs_to_jiffies(bfqq->bfqd->bfq_slice_idle) + 4);
}
/*
* Return the farthest future time instant according to jiffies
* macros.
*/
static unsigned long bfq_greatest_from_now(void)
{
return jiffies + MAX_JIFFY_OFFSET;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Return the farthest past time instant according to jiffies
* macros.
*/
static unsigned long bfq_smallest_from_now(void)
{
return jiffies - MAX_JIFFY_OFFSET;
}
/**
* bfq_bfqq_expire - expire a queue.
* @bfqd: device owning the queue.
* @bfqq: the queue to expire.
* @compensate: if true, compensate for the time spent idling.
* @reason: the reason causing the expiration.
*
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
* If the process associated with bfqq does slow I/O (e.g., because it
* issues random requests), we charge bfqq with the time it has been
* in service instead of the service it has received (see
* bfq_bfqq_charge_time for details on how this goal is achieved). As
* a consequence, bfqq will typically get higher timestamps upon
* reactivation, and hence it will be rescheduled as if it had
* received more service than what it has actually received. In the
* end, bfqq receives less service in proportion to how slowly its
* associated process consumes its budgets (and hence how seriously it
* tends to lower the throughput). In addition, this time-charging
* strategy guarantees time fairness among slow processes. In
* contrast, if the process associated with bfqq is not slow, we
* charge bfqq exactly with the service it has received.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
* Charging time to the first type of queues and the exact service to
* the other has the effect of using the WF2Q+ policy to schedule the
* former on a timeslice basis, without violating service domain
* guarantees among the latter.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_bfqq_expire(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
bool compensate,
enum bfqq_expiration reason)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
bool slow;
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
unsigned long delta = 0;
struct bfq_entity *entity = &bfqq->entity;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
int ref;
/*
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
* Check whether the process is slow (see bfq_bfqq_is_slow).
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
slow = bfq_bfqq_is_slow(bfqd, bfqq, compensate, reason, &delta);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
/*
* Increase service_from_backlogged before next statement,
* because the possible next invocation of
* bfq_bfqq_charge_time would likely inflate
* entity->service. In contrast, service_from_backlogged must
* contain real service, to enable the soft real-time
* heuristic to correctly compute the bandwidth consumed by
* bfqq.
*/
bfqq->service_from_backlogged += entity->service;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
* As above explained, charge slow (typically seeky) and
* timed-out queues with the time and not the service
* received, to favor sequential workloads.
*
* Processes doing I/O in the slower disk zones will tend to
* be slow(er) even if not seeky. Therefore, since the
* estimated peak rate is actually an average over the disk
* surface, these processes may timeout just for bad luck. To
* avoid punishing them, do not charge time to processes that
* succeeded in consuming at least 2/3 of their budget. This
* allows BFQ to preserve enough elasticity to still perform
* bandwidth, and not time, distribution with little unlucky
* or quasi-sequential processes.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqq->wr_coeff == 1 &&
(slow ||
(reason == BFQQE_BUDGET_TIMEOUT &&
bfq_bfqq_budget_left(bfqq) >= entity->budget / 3)))
block, bfq: add more fairness with writes and slow processes This patch deals with two sources of unfairness, which can also cause high latencies and throughput loss. The first source is related to write requests. Write requests tend to starve read requests, basically because, on one side, writes are slower than reads, whereas, on the other side, storage devices confuse schedulers by deceptively signaling the completion of write requests immediately after receiving them. This patch addresses this issue by just throttling writes. In particular, after a write request is dispatched for a queue, the budget of the queue is decremented by the number of sectors to write, multiplied by an (over)charge coefficient. The value of the coefficient is the result of our tuning with different devices. The second source of unfairness has to do with slowness detection: when the in-service queue is expired, BFQ also controls whether the queue has been "too slow", i.e., has consumed its last-assigned budget at such a low rate that it would have been impossible to consume all of this budget within the maximum time slice T_max (Subsec. 3.5 in [1]). In this case, the queue is always (over)charged the whole budget, to reduce its utilization of the device. Both this overcharge and the slowness-detection criterion may cause unfairness. First, always charging a full budget to a slow queue is too coarse. It is much more accurate, and this patch lets BFQ do so, to charge an amount of service 'equivalent' to the amount of time during which the queue has been in service. As explained in more detail in the comments on the code, this enables BFQ to provide time fairness among slow queues. Secondly, because of ZBR, a queue may be deemed as slow when its associated process is performing I/O on the slowest zones of a disk. However, unless the process is truly too slow, not reducing the disk utilization of the queue is more profitable in terms of disk throughput than the opposite. A similar problem is caused by logical block mapping on non-rotational devices. For this reason, this patch lets a queue be charged time, and not budget, only if the queue has consumed less than 2/3 of its assigned budget. As an additional, important benefit, this tolerance allows BFQ to preserve enough elasticity to still perform bandwidth, and not time, distribution with little unlucky or quasi-sequential processes. Finally, for the same reasons as above, this patch makes slowness detection itself much less harsh: a queue is deemed slow only if it has consumed its budget at less than half of the peak rate. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:11 +07:00
bfq_bfqq_charge_time(bfqd, bfqq, delta);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (reason == BFQQE_TOO_IDLE &&
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
entity->service <= 2 * entity->budget / 10)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_clear_bfqq_IO_bound(bfqq);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqd->low_latency && bfqq->wr_coeff == 1)
bfqq->last_wr_start_finish = jiffies;
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
if (bfqd->low_latency && bfqd->bfq_wr_max_softrt_rate > 0 &&
RB_EMPTY_ROOT(&bfqq->sort_list)) {
/*
* If we get here, and there are no outstanding
* requests, then the request pattern is isochronous
* (see the comments on the function
* bfq_bfqq_softrt_next_start()). Thus we can compute
* soft_rt_next_start. If, instead, the queue still
* has outstanding requests, then we have to wait for
* the completion of all the outstanding requests to
* discover whether the request pattern is actually
* isochronous.
*/
if (bfqq->dispatched == 0)
bfqq->soft_rt_next_start =
bfq_bfqq_softrt_next_start(bfqd, bfqq);
else {
/*
* The application is still waiting for the
* completion of one or more requests:
* prevent it from possibly being incorrectly
* deemed as soft real-time by setting its
* soft_rt_next_start to infinity. In fact,
* without this assignment, the application
* would be incorrectly deemed as soft
* real-time if:
* 1) it issued a new request before the
* completion of all its in-flight
* requests, and
* 2) at that time, its soft_rt_next_start
* happened to be in the past.
*/
bfqq->soft_rt_next_start =
bfq_greatest_from_now();
/*
* Schedule an update of soft_rt_next_start to when
* the task may be discovered to be isochronous.
*/
bfq_mark_bfqq_softrt_update(bfqq);
}
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq,
"expire (%d, slow %d, num_disp %d, idle_win %d)", reason,
slow, bfqq->dispatched, bfq_bfqq_idle_window(bfqq));
/*
* Increase, decrease or leave budget unchanged according to
* reason.
*/
__bfq_bfqq_recalc_budget(bfqd, bfqq, reason);
ref = bfqq->ref;
__bfq_bfqq_expire(bfqd, bfqq);
/* mark bfqq as waiting a request only if a bic still points to it */
if (ref > 1 && !bfq_bfqq_busy(bfqq) &&
reason != BFQQE_BUDGET_TIMEOUT &&
reason != BFQQE_BUDGET_EXHAUSTED)
bfq_mark_bfqq_non_blocking_wait_rq(bfqq);
}
/*
* Budget timeout is not implemented through a dedicated timer, but
* just checked on request arrivals and completions, as well as on
* idle timer expirations.
*/
static bool bfq_bfqq_budget_timeout(struct bfq_queue *bfqq)
{
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
return time_is_before_eq_jiffies(bfqq->budget_timeout);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
/*
* If we expire a queue that is actively waiting (i.e., with the
* device idled) for the arrival of a new request, then we may incur
* the timestamp misalignment problem described in the body of the
* function __bfq_activate_entity. Hence we return true only if this
* condition does not hold, or if the queue is slow enough to deserve
* only to be kicked off for preserving a high throughput.
*/
static bool bfq_may_expire_for_budg_timeout(struct bfq_queue *bfqq)
{
bfq_log_bfqq(bfqq->bfqd, bfqq,
"may_budget_timeout: wait_request %d left %d timeout %d",
bfq_bfqq_wait_request(bfqq),
bfq_bfqq_budget_left(bfqq) >= bfqq->entity.budget / 3,
bfq_bfqq_budget_timeout(bfqq));
return (!bfq_bfqq_wait_request(bfqq) ||
bfq_bfqq_budget_left(bfqq) >= bfqq->entity.budget / 3)
&&
bfq_bfqq_budget_timeout(bfqq);
}
/*
* For a queue that becomes empty, device idling is allowed only if
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* this function returns true for the queue. As a consequence, since
* device idling plays a critical role in both throughput boosting and
* service guarantees, the return value of this function plays a
* critical role in both these aspects as well.
*
* In a nutshell, this function returns true only if idling is
* beneficial for throughput or, even if detrimental for throughput,
* idling is however necessary to preserve service guarantees (low
* latency, desired throughput distribution, ...). In particular, on
* NCQ-capable devices, this function tries to return false, so as to
* help keep the drives' internal queues full, whenever this helps the
* device boost the throughput without causing any service-guarantee
* issue.
*
* In more detail, the return value of this function is obtained by,
* first, computing a number of boolean variables that take into
* account throughput and service-guarantee issues, and, then,
* combining these variables in a logical expression. Most of the
* issues taken into account are not trivial. We discuss these issues
* individually while introducing the variables.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
static bool bfq_bfqq_may_idle(struct bfq_queue *bfqq)
{
struct bfq_data *bfqd = bfqq->bfqd;
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
bool idling_boosts_thr, idling_boosts_thr_without_issues,
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
idling_needed_for_service_guarantees,
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
asymmetric_scenario;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (bfqd->strict_guarantees)
return true;
/*
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* The next variable takes into account the cases where idling
* boosts the throughput.
*
block, bfq: boost the throughput with random I/O on NCQ-capable HDDs This patch is basically the counterpart, for NCQ-capable rotational devices, of the previous patch. Exactly as the previous patch does on flash-based devices and for any workload, this patch disables device idling on rotational devices, but only for random I/O. In fact, only with these queues disabling idling boosts the throughput on NCQ-capable rotational devices. To not break service guarantees, idling is disabled for NCQ-enabled rotational devices only when the same symmetry conditions considered in the previous patches hold. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:19 +07:00
* The value of the variable is computed considering, first, that
* idling is virtually always beneficial for the throughput if:
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
* (a) the device is not NCQ-capable, or
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* (b) regardless of the presence of NCQ, the device is rotational
block, bfq: boost the throughput with random I/O on NCQ-capable HDDs This patch is basically the counterpart, for NCQ-capable rotational devices, of the previous patch. Exactly as the previous patch does on flash-based devices and for any workload, this patch disables device idling on rotational devices, but only for random I/O. In fact, only with these queues disabling idling boosts the throughput on NCQ-capable rotational devices. To not break service guarantees, idling is disabled for NCQ-enabled rotational devices only when the same symmetry conditions considered in the previous patches hold. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:19 +07:00
* and the request pattern for bfqq is I/O-bound and sequential.
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
*
* Secondly, and in contrast to the above item (b), idling an
* NCQ-capable flash-based device would not boost the
block, bfq: boost the throughput with random I/O on NCQ-capable HDDs This patch is basically the counterpart, for NCQ-capable rotational devices, of the previous patch. Exactly as the previous patch does on flash-based devices and for any workload, this patch disables device idling on rotational devices, but only for random I/O. In fact, only with these queues disabling idling boosts the throughput on NCQ-capable rotational devices. To not break service guarantees, idling is disabled for NCQ-enabled rotational devices only when the same symmetry conditions considered in the previous patches hold. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:19 +07:00
* throughput even with sequential I/O; rather it would lower
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* the throughput in proportion to how fast the device
* is. Accordingly, the next variable is true if any of the
* above conditions (a) and (b) is true, and, in particular,
* happens to be false if bfqd is an NCQ-capable flash-based
* device.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
idling_boosts_thr = !bfqd->hw_tag ||
block, bfq: boost the throughput with random I/O on NCQ-capable HDDs This patch is basically the counterpart, for NCQ-capable rotational devices, of the previous patch. Exactly as the previous patch does on flash-based devices and for any workload, this patch disables device idling on rotational devices, but only for random I/O. In fact, only with these queues disabling idling boosts the throughput on NCQ-capable rotational devices. To not break service guarantees, idling is disabled for NCQ-enabled rotational devices only when the same symmetry conditions considered in the previous patches hold. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:19 +07:00
(!blk_queue_nonrot(bfqd->queue) && bfq_bfqq_IO_bound(bfqq) &&
bfq_bfqq_idle_window(bfqq));
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
/*
* The value of the next variable,
* idling_boosts_thr_without_issues, is equal to that of
* idling_boosts_thr, unless a special case holds. In this
* special case, described below, idling may cause problems to
* weight-raised queues.
*
* When the request pool is saturated (e.g., in the presence
* of write hogs), if the processes associated with
* non-weight-raised queues ask for requests at a lower rate,
* then processes associated with weight-raised queues have a
* higher probability to get a request from the pool
* immediately (or at least soon) when they need one. Thus
* they have a higher probability to actually get a fraction
* of the device throughput proportional to their high
* weight. This is especially true with NCQ-capable drives,
* which enqueue several requests in advance, and further
* reorder internally-queued requests.
*
* For this reason, we force to false the value of
* idling_boosts_thr_without_issues if there are weight-raised
* busy queues. In this case, and if bfqq is not weight-raised,
* this guarantees that the device is not idled for bfqq (if,
* instead, bfqq is weight-raised, then idling will be
* guaranteed by another variable, see below). Combined with
* the timestamping rules of BFQ (see [1] for details), this
* behavior causes bfqq, and hence any sync non-weight-raised
* queue, to get a lower number of requests served, and thus
* to ask for a lower number of requests from the request
* pool, before the busy weight-raised queues get served
* again. This often mitigates starvation problems in the
* presence of heavy write workloads and NCQ, thereby
* guaranteeing a higher application and system responsiveness
* in these hostile scenarios.
*/
idling_boosts_thr_without_issues = idling_boosts_thr &&
bfqd->wr_busy_queues == 0;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* There is then a case where idling must be performed not
* for throughput concerns, but to preserve service
* guarantees.
*
* To introduce this case, we can note that allowing the drive
* to enqueue more than one request at a time, and hence
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* delegating de facto final scheduling decisions to the
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* drive's internal scheduler, entails loss of control on the
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* actual request service order. In particular, the critical
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* situation is when requests from different processes happen
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* to be present, at the same time, in the internal queue(s)
* of the drive. In such a situation, the drive, by deciding
* the service order of the internally-queued requests, does
* determine also the actual throughput distribution among
* these processes. But the drive typically has no notion or
* concern about per-process throughput distribution, and
* makes its decisions only on a per-request basis. Therefore,
* the service distribution enforced by the drive's internal
* scheduler is likely to coincide with the desired
* device-throughput distribution only in a completely
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* symmetric scenario where:
* (i) each of these processes must get the same throughput as
* the others;
* (ii) all these processes have the same I/O pattern
(either sequential or random).
* In fact, in such a scenario, the drive will tend to treat
* the requests of each of these processes in about the same
* way as the requests of the others, and thus to provide
* each of these processes with about the same throughput
* (which is exactly the desired throughput distribution). In
* contrast, in any asymmetric scenario, device idling is
* certainly needed to guarantee that bfqq receives its
* assigned fraction of the device throughput (see [1] for
* details).
*
* We address this issue by controlling, actually, only the
* symmetry sub-condition (i), i.e., provided that
* sub-condition (i) holds, idling is not performed,
* regardless of whether sub-condition (ii) holds. In other
* words, only if sub-condition (i) holds, then idling is
* allowed, and the device tends to be prevented from queueing
* many requests, possibly of several processes. The reason
* for not controlling also sub-condition (ii) is that we
* exploit preemption to preserve guarantees in case of
* symmetric scenarios, even if (ii) does not hold, as
* explained in the next two paragraphs.
*
* Even if a queue, say Q, is expired when it remains idle, Q
* can still preempt the new in-service queue if the next
* request of Q arrives soon (see the comments on
* bfq_bfqq_update_budg_for_activation). If all queues and
* groups have the same weight, this form of preemption,
* combined with the hole-recovery heuristic described in the
* comments on function bfq_bfqq_update_budg_for_activation,
* are enough to preserve a correct bandwidth distribution in
* the mid term, even without idling. In fact, even if not
* idling allows the internal queues of the device to contain
* many requests, and thus to reorder requests, we can rather
* safely assume that the internal scheduler still preserves a
* minimum of mid-term fairness. The motivation for using
* preemption instead of idling is that, by not idling,
* service guarantees are preserved without minimally
* sacrificing throughput. In other words, both a high
* throughput and its desired distribution are obtained.
*
* More precisely, this preemption-based, idleless approach
* provides fairness in terms of IOPS, and not sectors per
* second. This can be seen with a simple example. Suppose
* that there are two queues with the same weight, but that
* the first queue receives requests of 8 sectors, while the
* second queue receives requests of 1024 sectors. In
* addition, suppose that each of the two queues contains at
* most one request at a time, which implies that each queue
* always remains idle after it is served. Finally, after
* remaining idle, each queue receives very quickly a new
* request. It follows that the two queues are served
* alternatively, preempting each other if needed. This
* implies that, although both queues have the same weight,
* the queue with large requests receives a service that is
* 1024/8 times as high as the service received by the other
* queue.
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* On the other hand, device idling is performed, and thus
* pure sector-domain guarantees are provided, for the
* following queues, which are likely to need stronger
* throughput guarantees: weight-raised queues, and queues
* with a higher weight than other queues. When such queues
* are active, sub-condition (i) is false, which triggers
* device idling.
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* According to the above considerations, the next variable is
* true (only) if sub-condition (i) holds. To compute the
* value of this variable, we not only use the return value of
* the function bfq_symmetric_scenario(), but also check
* whether bfqq is being weight-raised, because
* bfq_symmetric_scenario() does not take into account also
* weight-raised queues (see comments on
* bfq_weights_tree_add()).
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*
* As a side note, it is worth considering that the above
* device-idling countermeasures may however fail in the
* following unlucky scenario: if idling is (correctly)
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
* disabled in a time period during which all symmetry
* sub-conditions hold, and hence the device is allowed to
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* enqueue many requests, but at some later point in time some
* sub-condition stops to hold, then it may become impossible
* to let requests be served in the desired order until all
* the requests already queued in the device have been served.
*/
block, bfq: boost the throughput on NCQ-capable flash-based devices This patch boosts the throughput on NCQ-capable flash-based devices, while still preserving latency guarantees for interactive and soft real-time applications. The throughput is boosted by just not idling the device when the in-service queue remains empty, even if the queue is sync and has a non-null idle window. This helps to keep the drive's internal queue full, which is necessary to achieve maximum performance. This solution to boost the throughput is a port of commits a68bbdd and f7d7b7a for CFQ. As already highlighted in a previous patch, allowing the device to prefetch and internally reorder requests trivially causes loss of control on the request service order, and hence on service guarantees. Fortunately, as discussed in detail in the comments on the function bfq_bfqq_may_idle(), if every process has to receive the same fraction of the throughput, then the service order enforced by the internal scheduler of a flash-based device is relatively close to that enforced by BFQ. In particular, it is close enough to let service guarantees be substantially preserved. Things change in an asymmetric scenario, i.e., if not every process has to receive the same fraction of the throughput. In this case, to guarantee the desired throughput distribution, the device must be prevented from prefetching requests. This is exactly what this patch does in asymmetric scenarios. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:18 +07:00
asymmetric_scenario = bfqq->wr_coeff > 1 ||
!bfq_symmetric_scenario(bfqd);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
/*
* Finally, there is a case where maximizing throughput is the
* best choice even if it may cause unfairness toward
* bfqq. Such a case is when bfqq became active in a burst of
* queue activations. Queues that became active during a large
* burst benefit only from throughput, as discussed in the
* comments on bfq_handle_burst. Thus, if bfqq became active
* in a burst and not idling the device maximizes throughput,
* then the device must no be idled, because not idling the
* device provides bfqq and all other queues in the burst with
* maximum benefit. Combining this and the above case, we can
* now establish when idling is actually needed to preserve
* service guarantees.
*/
idling_needed_for_service_guarantees =
asymmetric_scenario && !bfq_bfqq_in_large_burst(bfqq);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* We have now all the components we need to compute the return
* value of the function, which is true only if both the following
* conditions hold:
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
* 1) bfqq is sync, because idling make sense only for sync queues;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
* 2) idling either boosts the throughput (without issues), or
* is necessary to preserve service guarantees.
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
return bfq_bfqq_sync(bfqq) &&
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
(idling_boosts_thr_without_issues ||
idling_needed_for_service_guarantees);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
/*
* If the in-service queue is empty but the function bfq_bfqq_may_idle
* returns true, then:
* 1) the queue must remain in service and cannot be expired, and
* 2) the device must be idled to wait for the possible arrival of a new
* request for the queue.
* See the comments on the function bfq_bfqq_may_idle for the reasons
* why performing device idling is the best choice to boost the throughput
* and preserve service guarantees when bfq_bfqq_may_idle itself
* returns true.
*/
static bool bfq_bfqq_must_idle(struct bfq_queue *bfqq)
{
struct bfq_data *bfqd = bfqq->bfqd;
return RB_EMPTY_ROOT(&bfqq->sort_list) && bfqd->bfq_slice_idle != 0 &&
bfq_bfqq_may_idle(bfqq);
}
/*
* Select a queue for service. If we have a current queue in service,
* check whether to continue servicing it, or retrieve and set a new one.
*/
static struct bfq_queue *bfq_select_queue(struct bfq_data *bfqd)
{
struct bfq_queue *bfqq;
struct request *next_rq;
enum bfqq_expiration reason = BFQQE_BUDGET_TIMEOUT;
bfqq = bfqd->in_service_queue;
if (!bfqq)
goto new_queue;
bfq_log_bfqq(bfqd, bfqq, "select_queue: already in-service queue");
if (bfq_may_expire_for_budg_timeout(bfqq) &&
!bfq_bfqq_wait_request(bfqq) &&
!bfq_bfqq_must_idle(bfqq))
goto expire;
check_queue:
/*
* This loop is rarely executed more than once. Even when it
* happens, it is much more convenient to re-execute this loop
* than to return NULL and trigger a new dispatch to get a
* request served.
*/
next_rq = bfqq->next_rq;
/*
* If bfqq has requests queued and it has enough budget left to
* serve them, keep the queue, otherwise expire it.
*/
if (next_rq) {
if (bfq_serv_to_charge(next_rq, bfqq) >
bfq_bfqq_budget_left(bfqq)) {
/*
* Expire the queue for budget exhaustion,
* which makes sure that the next budget is
* enough to serve the next request, even if
* it comes from the fifo expired path.
*/
reason = BFQQE_BUDGET_EXHAUSTED;
goto expire;
} else {
/*
* The idle timer may be pending because we may
* not disable disk idling even when a new request
* arrives.
*/
if (bfq_bfqq_wait_request(bfqq)) {
/*
* If we get here: 1) at least a new request
* has arrived but we have not disabled the
* timer because the request was too small,
* 2) then the block layer has unplugged
* the device, causing the dispatch to be
* invoked.
*
* Since the device is unplugged, now the
* requests are probably large enough to
* provide a reasonable throughput.
* So we disable idling.
*/
bfq_clear_bfqq_wait_request(bfqq);
hrtimer_try_to_cancel(&bfqd->idle_slice_timer);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_update_idle_time(bfqq_group(bfqq));
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
goto keep_queue;
}
}
/*
* No requests pending. However, if the in-service queue is idling
* for a new request, or has requests waiting for a completion and
* may idle after their completion, then keep it anyway.
*/
if (bfq_bfqq_wait_request(bfqq) ||
(bfqq->dispatched != 0 && bfq_bfqq_may_idle(bfqq))) {
bfqq = NULL;
goto keep_queue;
}
reason = BFQQE_NO_MORE_REQUESTS;
expire:
bfq_bfqq_expire(bfqd, bfqq, false, reason);
new_queue:
bfqq = bfq_set_in_service_queue(bfqd);
if (bfqq) {
bfq_log_bfqq(bfqd, bfqq, "select_queue: checking new queue");
goto check_queue;
}
keep_queue:
if (bfqq)
bfq_log_bfqq(bfqd, bfqq, "select_queue: returned this queue");
else
bfq_log(bfqd, "select_queue: no queue returned");
return bfqq;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
static void bfq_update_wr_data(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
struct bfq_entity *entity = &bfqq->entity;
if (bfqq->wr_coeff > 1) { /* queue is being weight-raised */
bfq_log_bfqq(bfqd, bfqq,
"raising period dur %u/%u msec, old coeff %u, w %d(%d)",
jiffies_to_msecs(jiffies - bfqq->last_wr_start_finish),
jiffies_to_msecs(bfqq->wr_cur_max_time),
bfqq->wr_coeff,
bfqq->entity.weight, bfqq->entity.orig_weight);
if (entity->prio_changed)
bfq_log_bfqq(bfqd, bfqq, "WARN: pending prio change");
/*
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
* If the queue was activated in a burst, or too much
* time has elapsed from the beginning of this
* weight-raising period, then end weight raising.
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
*/
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
if (bfq_bfqq_in_large_burst(bfqq))
bfq_bfqq_end_wr(bfqq);
else if (time_is_before_jiffies(bfqq->last_wr_start_finish +
bfqq->wr_cur_max_time)) {
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
if (bfqq->wr_cur_max_time != bfqd->bfq_wr_rt_max_time ||
time_is_before_jiffies(bfqq->wr_start_at_switch_to_srt +
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bfq_wr_duration(bfqd)))
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfq_bfqq_end_wr(bfqq);
else {
/* switch back to interactive wr */
bfqq->wr_coeff = bfqd->bfq_wr_coeff;
bfqq->wr_cur_max_time = bfq_wr_duration(bfqd);
bfqq->last_wr_start_finish =
bfqq->wr_start_at_switch_to_srt;
bfqq->entity.prio_changed = 1;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
}
/* Update weight both if it must be raised and if it must be lowered */
if ((entity->weight > entity->orig_weight) != (bfqq->wr_coeff > 1))
__bfq_entity_update_weight_prio(
bfq_entity_service_tree(entity),
entity);
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Dispatch next request from bfqq.
*/
static struct request *bfq_dispatch_rq_from_bfqq(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
struct request *rq = bfqq->next_rq;
unsigned long service_to_charge;
service_to_charge = bfq_serv_to_charge(rq, bfqq);
bfq_bfqq_served(bfqq, service_to_charge);
bfq_dispatch_remove(bfqd->queue, rq);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* If weight raising has to terminate for bfqq, then next
* function causes an immediate update of bfqq's weight,
* without waiting for next activation. As a consequence, on
* expiration, bfqq will be timestamped as if has never been
* weight-raised during this service slot, even if it has
* received part or even most of the service as a
* weight-raised queue. This inflates bfqq's timestamps, which
* is beneficial, as bfqq is then more willing to leave the
* device immediately to possible other weight-raised queues.
*/
bfq_update_wr_data(bfqd, bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Expire bfqq, pretending that its budget expired, if bfqq
* belongs to CLASS_IDLE and other queues are waiting for
* service.
*/
if (bfqd->busy_queues > 1 && bfq_class_idle(bfqq))
goto expire;
return rq;
expire:
bfq_bfqq_expire(bfqd, bfqq, false, BFQQE_BUDGET_EXHAUSTED);
return rq;
}
static bool bfq_has_work(struct blk_mq_hw_ctx *hctx)
{
struct bfq_data *bfqd = hctx->queue->elevator->elevator_data;
/*
* Avoiding lock: a race on bfqd->busy_queues should cause at
* most a call to dispatch for nothing
*/
return !list_empty_careful(&bfqd->dispatch) ||
bfqd->busy_queues > 0;
}
static struct request *__bfq_dispatch_request(struct blk_mq_hw_ctx *hctx)
{
struct bfq_data *bfqd = hctx->queue->elevator->elevator_data;
struct request *rq = NULL;
struct bfq_queue *bfqq = NULL;
if (!list_empty(&bfqd->dispatch)) {
rq = list_first_entry(&bfqd->dispatch, struct request,
queuelist);
list_del_init(&rq->queuelist);
bfqq = RQ_BFQQ(rq);
if (bfqq) {
/*
* Increment counters here, because this
* dispatch does not follow the standard
* dispatch flow (where counters are
* incremented)
*/
bfqq->dispatched++;
goto inc_in_driver_start_rq;
}
/*
* We exploit the put_rq_private hook to decrement
* rq_in_driver, but put_rq_private will not be
* invoked on this request. So, to avoid unbalance,
* just start this request, without incrementing
* rq_in_driver. As a negative consequence,
* rq_in_driver is deceptively lower than it should be
* while this request is in service. This may cause
* bfq_schedule_dispatch to be invoked uselessly.
*
* As for implementing an exact solution, the
* put_request hook, if defined, is probably invoked
* also on this request. So, by exploiting this hook,
* we could 1) increment rq_in_driver here, and 2)
* decrement it in put_request. Such a solution would
* let the value of the counter be always accurate,
* but it would entail using an extra interface
* function. This cost seems higher than the benefit,
* being the frequency of non-elevator-private
* requests very low.
*/
goto start_rq;
}
bfq_log(bfqd, "dispatch requests: %d busy queues", bfqd->busy_queues);
if (bfqd->busy_queues == 0)
goto exit;
/*
* Force device to serve one request at a time if
* strict_guarantees is true. Forcing this service scheme is
* currently the ONLY way to guarantee that the request
* service order enforced by the scheduler is respected by a
* queueing device. Otherwise the device is free even to make
* some unlucky request wait for as long as the device
* wishes.
*
* Of course, serving one request at at time may cause loss of
* throughput.
*/
if (bfqd->strict_guarantees && bfqd->rq_in_driver > 0)
goto exit;
bfqq = bfq_select_queue(bfqd);
if (!bfqq)
goto exit;
rq = bfq_dispatch_rq_from_bfqq(bfqd, bfqq);
if (rq) {
inc_in_driver_start_rq:
bfqd->rq_in_driver++;
start_rq:
rq->rq_flags |= RQF_STARTED;
}
exit:
return rq;
}
static struct request *bfq_dispatch_request(struct blk_mq_hw_ctx *hctx)
{
struct bfq_data *bfqd = hctx->queue->elevator->elevator_data;
struct request *rq;
spin_lock_irq(&bfqd->lock);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
rq = __bfq_dispatch_request(hctx);
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irq(&bfqd->lock);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return rq;
}
/*
* Task holds one reference to the queue, dropped when task exits. Each rq
* in-flight on this queue also holds a reference, dropped when rq is freed.
*
* Scheduler lock must be held here. Recall not to use bfqq after calling
* this function on it.
*/
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_put_queue(struct bfq_queue *bfqq)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
struct bfq_group *bfqg = bfqq_group(bfqq);
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (bfqq->bfqd)
bfq_log_bfqq(bfqq->bfqd, bfqq, "put_queue: %p %d",
bfqq, bfqq->ref);
bfqq->ref--;
if (bfqq->ref)
return;
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
if (bfq_bfqq_sync(bfqq))
/*
* The fact that this queue is being destroyed does not
* invalidate the fact that this queue may have been
* activated during the current burst. As a consequence,
* although the queue does not exist anymore, and hence
* needs to be removed from the burst list if there,
* the burst size has not to be decremented.
*/
hlist_del_init(&bfqq->burst_list_node);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
kmem_cache_free(bfq_pool, bfqq);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
bfqg_put(bfqg);
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
static void bfq_put_cooperator(struct bfq_queue *bfqq)
{
struct bfq_queue *__bfqq, *next;
/*
* If this queue was scheduled to merge with another queue, be
* sure to drop the reference taken on that queue (and others in
* the merge chain). See bfq_setup_merge and bfq_merge_bfqqs.
*/
__bfqq = bfqq->new_bfqq;
while (__bfqq) {
if (__bfqq == bfqq)
break;
next = __bfqq->new_bfqq;
bfq_put_queue(__bfqq);
__bfqq = next;
}
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static void bfq_exit_bfqq(struct bfq_data *bfqd, struct bfq_queue *bfqq)
{
if (bfqq == bfqd->in_service_queue) {
__bfq_bfqq_expire(bfqd, bfqq);
bfq_schedule_dispatch(bfqd);
}
bfq_log_bfqq(bfqd, bfqq, "exit_bfqq: %p, %d", bfqq, bfqq->ref);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfq_put_cooperator(bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_put_queue(bfqq); /* release process reference */
}
static void bfq_exit_icq_bfqq(struct bfq_io_cq *bic, bool is_sync)
{
struct bfq_queue *bfqq = bic_to_bfqq(bic, is_sync);
struct bfq_data *bfqd;
if (bfqq)
bfqd = bfqq->bfqd; /* NULL if scheduler already exited */
if (bfqq && bfqd) {
unsigned long flags;
spin_lock_irqsave(&bfqd->lock, flags);
bfq_exit_bfqq(bfqd, bfqq);
bic_set_bfqq(bic, NULL, is_sync);
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irqrestore(&bfqd->lock, flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
}
static void bfq_exit_icq(struct io_cq *icq)
{
struct bfq_io_cq *bic = icq_to_bic(icq);
bfq_exit_icq_bfqq(bic, true);
bfq_exit_icq_bfqq(bic, false);
}
/*
* Update the entity prio values; note that the new values will not
* be used until the next (re)activation.
*/
static void
bfq_set_next_ioprio_data(struct bfq_queue *bfqq, struct bfq_io_cq *bic)
{
struct task_struct *tsk = current;
int ioprio_class;
struct bfq_data *bfqd = bfqq->bfqd;
if (!bfqd)
return;
ioprio_class = IOPRIO_PRIO_CLASS(bic->ioprio);
switch (ioprio_class) {
default:
dev_err(bfqq->bfqd->queue->backing_dev_info->dev,
"bfq: bad prio class %d\n", ioprio_class);
case IOPRIO_CLASS_NONE:
/*
* No prio set, inherit CPU scheduling settings.
*/
bfqq->new_ioprio = task_nice_ioprio(tsk);
bfqq->new_ioprio_class = task_nice_ioclass(tsk);
break;
case IOPRIO_CLASS_RT:
bfqq->new_ioprio = IOPRIO_PRIO_DATA(bic->ioprio);
bfqq->new_ioprio_class = IOPRIO_CLASS_RT;
break;
case IOPRIO_CLASS_BE:
bfqq->new_ioprio = IOPRIO_PRIO_DATA(bic->ioprio);
bfqq->new_ioprio_class = IOPRIO_CLASS_BE;
break;
case IOPRIO_CLASS_IDLE:
bfqq->new_ioprio_class = IOPRIO_CLASS_IDLE;
bfqq->new_ioprio = 7;
bfq_clear_bfqq_idle_window(bfqq);
break;
}
if (bfqq->new_ioprio >= IOPRIO_BE_NR) {
pr_crit("bfq_set_next_ioprio_data: new_ioprio %d\n",
bfqq->new_ioprio);
bfqq->new_ioprio = IOPRIO_BE_NR;
}
bfqq->entity.new_weight = bfq_ioprio_to_weight(bfqq->new_ioprio);
bfqq->entity.prio_changed = 1;
}
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
static struct bfq_queue *bfq_get_queue(struct bfq_data *bfqd,
struct bio *bio, bool is_sync,
struct bfq_io_cq *bic);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static void bfq_check_ioprio_change(struct bfq_io_cq *bic, struct bio *bio)
{
struct bfq_data *bfqd = bic_to_bfqd(bic);
struct bfq_queue *bfqq;
int ioprio = bic->icq.ioc->ioprio;
/*
* This condition may trigger on a newly created bic, be sure to
* drop the lock before returning.
*/
if (unlikely(!bfqd) || likely(bic->ioprio == ioprio))
return;
bic->ioprio = ioprio;
bfqq = bic_to_bfqq(bic, false);
if (bfqq) {
/* release process reference on this queue */
bfq_put_queue(bfqq);
bfqq = bfq_get_queue(bfqd, bio, BLK_RW_ASYNC, bic);
bic_set_bfqq(bic, bfqq, false);
}
bfqq = bic_to_bfqq(bic, true);
if (bfqq)
bfq_set_next_ioprio_data(bfqq, bic);
}
static void bfq_init_bfqq(struct bfq_data *bfqd, struct bfq_queue *bfqq,
struct bfq_io_cq *bic, pid_t pid, int is_sync)
{
RB_CLEAR_NODE(&bfqq->entity.rb_node);
INIT_LIST_HEAD(&bfqq->fifo);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
INIT_HLIST_NODE(&bfqq->burst_list_node);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfqq->ref = 0;
bfqq->bfqd = bfqd;
if (bic)
bfq_set_next_ioprio_data(bfqq, bic);
if (is_sync) {
if (!bfq_class_idle(bfqq))
bfq_mark_bfqq_idle_window(bfqq);
bfq_mark_bfqq_sync(bfqq);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bfq_mark_bfqq_just_created(bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
} else
bfq_clear_bfqq_sync(bfqq);
/* set end request to minus infinity from now */
bfqq->ttime.last_end_request = ktime_get_ns() + 1;
bfq_mark_bfqq_IO_bound(bfqq);
bfqq->pid = pid;
/* Tentative initial value to trade off between thr and lat */
block, bfq: improve throughput boosting The feedback-loop algorithm used by BFQ to compute queue (process) budgets is basically a set of three update rules, one for each of the main reasons why a queue may be expired. If many processes suddenly switch from sporadic I/O to greedy and sequential I/O, then these rules are quite slow to assign large budgets to these processes, and hence to achieve a high throughput. On the opposite side, BFQ assigns the maximum possible budget B_max to a just-created queue. This allows a high throughput to be achieved immediately if the associated process is I/O-bound and performs sequential I/O from the beginning. But it also increases the worst-case latency experienced by the first requests issued by the process, because the larger the budget of a queue waiting for service is, the later the queue will be served by B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or soft real-time application. To tackle these throughput and latency problems, on one hand this patch changes the initial budget value to B_max/2. On the other hand, it re-tunes the three rules, adopting a more aggressive, multiplicative increase/linear decrease scheme. This scheme trades latency for throughput more than before, and tends to assign large budgets quickly to processes that are or become I/O-bound. For two of the expiration reasons, the new version of the rules also contains some more little improvements, briefly described below. *No more backlog.* In this case, the budget was larger than the number of sectors actually read/written by the process before it stopped doing I/O. Hence, to reduce latency for the possible future I/O requests of the process, the old rule simply set the next budget to the number of sectors actually consumed by the process. However, if there are still outstanding requests, then the process may have not yet issued its next request just because it is still waiting for the completion of some of the still outstanding ones. If this sub-case holds true, then the new rule, instead of decreasing the budget, doubles it, proactively, in the hope that: 1) a larger budget will fit the actual needs of the process, and 2) the process is sequential and hence a higher throughput will be achieved by serving the process longer after granting it access to the device. *Budget timeout*. The original rule set the new budget to the maximum value B_max, to maximize throughput and let all processes experiencing budget timeouts receive the same share of the device time. In our experiments we verified that this sudden jump to B_max did not provide sensible benefits; rather it increased the latency of processes performing sporadic and short I/O. The new rule only doubles the budget. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:09 +07:00
bfqq->max_budget = (2 * bfq_max_budget(bfqd)) / 3;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfqq->budget_timeout = bfq_smallest_from_now();
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqq->wr_coeff = 1;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfqq->last_wr_start_finish = jiffies;
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqq->wr_start_at_switch_to_srt = bfq_smallest_from_now();
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfqq->split_time = bfq_smallest_from_now();
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
/*
* Set to the value for which bfqq will not be deemed as
* soft rt when it becomes backlogged.
*/
bfqq->soft_rt_next_start = bfq_greatest_from_now();
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/* first request is almost certainly seeky */
bfqq->seek_history = 1;
}
static struct bfq_queue **bfq_async_queue_prio(struct bfq_data *bfqd,
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
struct bfq_group *bfqg,
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
int ioprio_class, int ioprio)
{
switch (ioprio_class) {
case IOPRIO_CLASS_RT:
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
return &bfqg->async_bfqq[0][ioprio];
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
case IOPRIO_CLASS_NONE:
ioprio = IOPRIO_NORM;
/* fall through */
case IOPRIO_CLASS_BE:
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
return &bfqg->async_bfqq[1][ioprio];
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
case IOPRIO_CLASS_IDLE:
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
return &bfqg->async_idle_bfqq;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
default:
return NULL;
}
}
static struct bfq_queue *bfq_get_queue(struct bfq_data *bfqd,
struct bio *bio, bool is_sync,
struct bfq_io_cq *bic)
{
const int ioprio = IOPRIO_PRIO_DATA(bic->ioprio);
const int ioprio_class = IOPRIO_PRIO_CLASS(bic->ioprio);
struct bfq_queue **async_bfqq = NULL;
struct bfq_queue *bfqq;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
struct bfq_group *bfqg;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
rcu_read_lock();
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg = bfq_find_set_group(bfqd, bio_blkcg(bio));
if (!bfqg) {
bfqq = &bfqd->oom_bfqq;
goto out;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (!is_sync) {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
async_bfqq = bfq_async_queue_prio(bfqd, bfqg, ioprio_class,
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
ioprio);
bfqq = *async_bfqq;
if (bfqq)
goto out;
}
bfqq = kmem_cache_alloc_node(bfq_pool,
GFP_NOWAIT | __GFP_ZERO | __GFP_NOWARN,
bfqd->queue->node);
if (bfqq) {
bfq_init_bfqq(bfqd, bfqq, bic, current->pid,
is_sync);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_init_entity(&bfqq->entity, bfqg);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq, "allocated");
} else {
bfqq = &bfqd->oom_bfqq;
bfq_log_bfqq(bfqd, bfqq, "using oom bfqq");
goto out;
}
/*
* Pin the queue now that it's allocated, scheduler exit will
* prune it.
*/
if (async_bfqq) {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqq->ref++; /*
* Extra group reference, w.r.t. sync
* queue. This extra reference is removed
* only if bfqq->bfqg disappears, to
* guarantee that this queue is not freed
* until its group goes away.
*/
bfq_log_bfqq(bfqd, bfqq, "get_queue, bfqq not in async: %p, %d",
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfqq, bfqq->ref);
*async_bfqq = bfqq;
}
out:
bfqq->ref++; /* get a process reference to this queue */
bfq_log_bfqq(bfqd, bfqq, "get_queue, at end: %p, %d", bfqq, bfqq->ref);
rcu_read_unlock();
return bfqq;
}
static void bfq_update_io_thinktime(struct bfq_data *bfqd,
struct bfq_queue *bfqq)
{
struct bfq_ttime *ttime = &bfqq->ttime;
u64 elapsed = ktime_get_ns() - bfqq->ttime.last_end_request;
elapsed = min_t(u64, elapsed, 2ULL * bfqd->bfq_slice_idle);
ttime->ttime_samples = (7*bfqq->ttime.ttime_samples + 256) / 8;
ttime->ttime_total = div_u64(7*ttime->ttime_total + 256*elapsed, 8);
ttime->ttime_mean = div64_ul(ttime->ttime_total + 128,
ttime->ttime_samples);
}
static void
bfq_update_io_seektime(struct bfq_data *bfqd, struct bfq_queue *bfqq,
struct request *rq)
{
bfqq->seek_history <<= 1;
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
bfqq->seek_history |=
get_sdist(bfqq->last_request_pos, rq) > BFQQ_SEEK_THR &&
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
(!blk_queue_nonrot(bfqd->queue) ||
blk_rq_sectors(rq) < BFQQ_SECT_THR_NONROT);
}
/*
* Disable idle window if the process thinks too long or seeks so much that
* it doesn't matter.
*/
static void bfq_update_idle_window(struct bfq_data *bfqd,
struct bfq_queue *bfqq,
struct bfq_io_cq *bic)
{
int enable_idle;
/* Don't idle for async or idle io prio class. */
if (!bfq_bfqq_sync(bfqq) || bfq_class_idle(bfqq))
return;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/* Idle window just restored, statistics are meaningless. */
if (time_is_after_eq_jiffies(bfqq->split_time +
bfqd->bfq_wr_min_idle_time))
return;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
enable_idle = bfq_bfqq_idle_window(bfqq);
if (atomic_read(&bic->icq.ioc->active_ref) == 0 ||
bfqd->bfq_slice_idle == 0 ||
block, bfq: preserve a low latency also with NCQ-capable drives I/O schedulers typically allow NCQ-capable drives to prefetch I/O requests, as NCQ boosts the throughput exactly by prefetching and internally reordering requests. Unfortunately, as discussed in detail and shown experimentally in [1], this may cause fairness and latency guarantees to be violated. The main problem is that the internal scheduler of an NCQ-capable drive may postpone the service of some unlucky (prefetched) requests as long as it deems serving other requests more appropriate to boost the throughput. This patch addresses this issue by not disabling device idling for weight-raised queues, even if the device supports NCQ. This allows BFQ to start serving a new queue, and therefore allows the drive to prefetch new requests, only after the idling timeout expires. At that time, all the outstanding requests of the expired queue have been most certainly served. [1] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:14 +07:00
(bfqd->hw_tag && BFQQ_SEEKY(bfqq) &&
bfqq->wr_coeff == 1))
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
enable_idle = 0;
else if (bfq_sample_valid(bfqq->ttime.ttime_samples)) {
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqq->ttime.ttime_mean > bfqd->bfq_slice_idle &&
bfqq->wr_coeff == 1)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
enable_idle = 0;
else
enable_idle = 1;
}
bfq_log_bfqq(bfqd, bfqq, "update_idle_window: enable_idle %d",
enable_idle);
if (enable_idle)
bfq_mark_bfqq_idle_window(bfqq);
else
bfq_clear_bfqq_idle_window(bfqq);
}
/*
* Called when a new fs request (rq) is added to bfqq. Check if there's
* something we should do about it.
*/
static void bfq_rq_enqueued(struct bfq_data *bfqd, struct bfq_queue *bfqq,
struct request *rq)
{
struct bfq_io_cq *bic = RQ_BIC(rq);
if (rq->cmd_flags & REQ_META)
bfqq->meta_pending++;
bfq_update_io_thinktime(bfqd, bfqq);
bfq_update_io_seektime(bfqd, bfqq, rq);
if (bfqq->entity.service > bfq_max_budget(bfqd) / 8 ||
!BFQQ_SEEKY(bfqq))
bfq_update_idle_window(bfqd, bfqq, bic);
bfq_log_bfqq(bfqd, bfqq,
"rq_enqueued: idle_window=%d (seeky %d)",
bfq_bfqq_idle_window(bfqq), BFQQ_SEEKY(bfqq));
bfqq->last_request_pos = blk_rq_pos(rq) + blk_rq_sectors(rq);
if (bfqq == bfqd->in_service_queue && bfq_bfqq_wait_request(bfqq)) {
bool small_req = bfqq->queued[rq_is_sync(rq)] == 1 &&
blk_rq_sectors(rq) < 32;
bool budget_timeout = bfq_bfqq_budget_timeout(bfqq);
/*
* There is just this request queued: if the request
* is small and the queue is not to be expired, then
* just exit.
*
* In this way, if the device is being idled to wait
* for a new request from the in-service queue, we
* avoid unplugging the device and committing the
* device to serve just a small request. On the
* contrary, we wait for the block layer to decide
* when to unplug the device: hopefully, new requests
* will be merged to this one quickly, then the device
* will be unplugged and larger requests will be
* dispatched.
*/
if (small_req && !budget_timeout)
return;
/*
* A large enough request arrived, or the queue is to
* be expired: in both cases disk idling is to be
* stopped, so clear wait_request flag and reset
* timer.
*/
bfq_clear_bfqq_wait_request(bfqq);
hrtimer_try_to_cancel(&bfqd->idle_slice_timer);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfqg_stats_update_idle_time(bfqq_group(bfqq));
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* The queue is not empty, because a new request just
* arrived. Hence we can safely expire the queue, in
* case of budget timeout, without risking that the
* timestamps of the queue are not updated correctly.
* See [1] for more details.
*/
if (budget_timeout)
bfq_bfqq_expire(bfqd, bfqq, false,
BFQQE_BUDGET_TIMEOUT);
}
}
static void __bfq_insert_request(struct bfq_data *bfqd, struct request *rq)
{
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
struct bfq_queue *bfqq = RQ_BFQQ(rq),
*new_bfqq = bfq_setup_cooperator(bfqd, bfqq, rq, true);
if (new_bfqq) {
if (bic_to_bfqq(RQ_BIC(rq), 1) != bfqq)
new_bfqq = bic_to_bfqq(RQ_BIC(rq), 1);
/*
* Release the request's reference to the old bfqq
* and make sure one is taken to the shared queue.
*/
new_bfqq->allocated++;
bfqq->allocated--;
new_bfqq->ref++;
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bfq_clear_bfqq_just_created(bfqq);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* If the bic associated with the process
* issuing this request still points to bfqq
* (and thus has not been already redirected
* to new_bfqq or even some other bfq_queue),
* then complete the merge and redirect it to
* new_bfqq.
*/
if (bic_to_bfqq(RQ_BIC(rq), 1) == bfqq)
bfq_merge_bfqqs(bfqd, RQ_BIC(rq),
bfqq, new_bfqq);
/*
* rq is about to be enqueued into new_bfqq,
* release rq reference on bfqq
*/
bfq_put_queue(bfqq);
rq->elv.priv[1] = new_bfqq;
bfqq = new_bfqq;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_add_request(rq);
rq->fifo_time = ktime_get_ns() + bfqd->bfq_fifo_expire[rq_is_sync(rq)];
list_add_tail(&rq->queuelist, &bfqq->fifo);
bfq_rq_enqueued(bfqd, bfqq, rq);
}
static void bfq_insert_request(struct blk_mq_hw_ctx *hctx, struct request *rq,
bool at_head)
{
struct request_queue *q = hctx->queue;
struct bfq_data *bfqd = q->elevator->elevator_data;
spin_lock_irq(&bfqd->lock);
if (blk_mq_sched_try_insert_merge(q, rq)) {
spin_unlock_irq(&bfqd->lock);
return;
}
spin_unlock_irq(&bfqd->lock);
blk_mq_sched_request_inserted(rq);
spin_lock_irq(&bfqd->lock);
if (at_head || blk_rq_is_passthrough(rq)) {
if (at_head)
list_add(&rq->queuelist, &bfqd->dispatch);
else
list_add_tail(&rq->queuelist, &bfqd->dispatch);
} else {
__bfq_insert_request(bfqd, rq);
if (rq_mergeable(rq)) {
elv_rqhash_add(q, rq);
if (!q->last_merge)
q->last_merge = rq;
}
}
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irq(&bfqd->lock);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static void bfq_insert_requests(struct blk_mq_hw_ctx *hctx,
struct list_head *list, bool at_head)
{
while (!list_empty(list)) {
struct request *rq;
rq = list_first_entry(list, struct request, queuelist);
list_del_init(&rq->queuelist);
bfq_insert_request(hctx, rq, at_head);
}
}
static void bfq_update_hw_tag(struct bfq_data *bfqd)
{
bfqd->max_rq_in_driver = max_t(int, bfqd->max_rq_in_driver,
bfqd->rq_in_driver);
if (bfqd->hw_tag == 1)
return;
/*
* This sample is valid if the number of outstanding requests
* is large enough to allow a queueing behavior. Note that the
* sum is not exact, as it's not taking into account deactivated
* requests.
*/
if (bfqd->rq_in_driver + bfqd->queued < BFQ_HW_QUEUE_THRESHOLD)
return;
if (bfqd->hw_tag_samples++ < BFQ_HW_QUEUE_SAMPLES)
return;
bfqd->hw_tag = bfqd->max_rq_in_driver > BFQ_HW_QUEUE_THRESHOLD;
bfqd->max_rq_in_driver = 0;
bfqd->hw_tag_samples = 0;
}
static void bfq_completed_request(struct bfq_queue *bfqq, struct bfq_data *bfqd)
{
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
u64 now_ns;
u32 delta_us;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_update_hw_tag(bfqd);
bfqd->rq_in_driver--;
bfqq->dispatched--;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (!bfqq->dispatched && !bfq_bfqq_busy(bfqq)) {
/*
* Set budget_timeout (which we overload to store the
* time at which the queue remains with no backlog and
* no outstanding request; used by the weight-raising
* mechanism).
*/
bfqq->budget_timeout = jiffies;
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
bfq_weights_tree_remove(bfqd, &bfqq->entity,
&bfqd->queue_weights_tree);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
}
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
now_ns = ktime_get_ns();
bfqq->ttime.last_end_request = now_ns;
/*
* Using us instead of ns, to get a reasonable precision in
* computing rate in next check.
*/
delta_us = div_u64(now_ns - bfqd->last_completion, NSEC_PER_USEC);
/*
* If the request took rather long to complete, and, according
* to the maximum request size recorded, this completion latency
* implies that the request was certainly served at a very low
* rate (less than 1M sectors/sec), then the whole observation
* interval that lasts up to this time instant cannot be a
* valid time interval for computing a new peak rate. Invoke
* bfq_update_rate_reset to have the following three steps
* taken:
* - close the observation interval at the last (previous)
* request dispatch or completion
* - compute rate, if possible, for that observation interval
* - reset to zero samples, which will trigger a proper
* re-initialization of the observation interval on next
* dispatch
*/
if (delta_us > BFQ_MIN_TT/NSEC_PER_USEC &&
(bfqd->last_rq_max_size<<BFQ_RATE_SHIFT)/delta_us <
1UL<<(BFQ_RATE_SHIFT - 10))
bfq_update_rate_reset(bfqd, NULL);
bfqd->last_completion = now_ns;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
/*
* If we are waiting to discover whether the request pattern
* of the task associated with the queue is actually
* isochronous, and both requisites for this condition to hold
* are now satisfied, then compute soft_rt_next_start (see the
* comments on the function bfq_bfqq_softrt_next_start()). We
* schedule this delayed check when bfqq expires, if it still
* has in-flight requests.
*/
if (bfq_bfqq_softrt_update(bfqq) && bfqq->dispatched == 0 &&
RB_EMPTY_ROOT(&bfqq->sort_list))
bfqq->soft_rt_next_start =
bfq_bfqq_softrt_next_start(bfqd, bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* If this is the in-service queue, check if it needs to be expired,
* or if we want to idle in case it has no pending requests.
*/
if (bfqd->in_service_queue == bfqq) {
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
if (bfqq->dispatched == 0 && bfq_bfqq_must_idle(bfqq)) {
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_arm_slice_timer(bfqd);
return;
} else if (bfq_may_expire_for_budg_timeout(bfqq))
bfq_bfqq_expire(bfqd, bfqq, false,
BFQQE_BUDGET_TIMEOUT);
else if (RB_EMPTY_ROOT(&bfqq->sort_list) &&
(bfqq->dispatched == 0 ||
!bfq_bfqq_may_idle(bfqq)))
bfq_bfqq_expire(bfqd, bfqq, false,
BFQQE_NO_MORE_REQUESTS);
}
}
static void bfq_put_rq_priv_body(struct bfq_queue *bfqq)
{
bfqq->allocated--;
bfq_put_queue(bfqq);
}
static void bfq_put_rq_private(struct request_queue *q, struct request *rq)
{
struct bfq_queue *bfqq = RQ_BFQQ(rq);
struct bfq_data *bfqd = bfqq->bfqd;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
if (rq->rq_flags & RQF_STARTED)
bfqg_stats_update_completion(bfqq_group(bfqq),
rq_start_time_ns(rq),
rq_io_start_time_ns(rq),
rq->cmd_flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
if (likely(rq->rq_flags & RQF_STARTED)) {
unsigned long flags;
spin_lock_irqsave(&bfqd->lock, flags);
bfq_completed_request(bfqq, bfqd);
bfq_put_rq_priv_body(bfqq);
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irqrestore(&bfqd->lock, flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
} else {
/*
* Request rq may be still/already in the scheduler,
* in which case we need to remove it. And we cannot
* defer such a check and removal, to avoid
* inconsistencies in the time interval from the end
* of this function to the start of the deferred work.
* This situation seems to occur only in process
* context, as a consequence of a merge. In the
* current version of the code, this implies that the
* lock is held.
*/
if (!RB_EMPTY_NODE(&rq->rb_node))
bfq_remove_request(q, rq);
bfq_put_rq_priv_body(bfqq);
}
rq->elv.priv[0] = NULL;
rq->elv.priv[1] = NULL;
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* Returns NULL if a new bfqq should be allocated, or the old bfqq if this
* was the last process referring to that bfqq.
*/
static struct bfq_queue *
bfq_split_bfqq(struct bfq_io_cq *bic, struct bfq_queue *bfqq)
{
bfq_log_bfqq(bfqq->bfqd, bfqq, "splitting queue");
if (bfqq_process_refs(bfqq) == 1) {
bfqq->pid = current->pid;
bfq_clear_bfqq_coop(bfqq);
bfq_clear_bfqq_split_coop(bfqq);
return bfqq;
}
bic_set_bfqq(bic, NULL, 1);
bfq_put_cooperator(bfqq);
bfq_put_queue(bfqq);
return NULL;
}
static struct bfq_queue *bfq_get_bfqq_handle_split(struct bfq_data *bfqd,
struct bfq_io_cq *bic,
struct bio *bio,
bool split, bool is_sync,
bool *new_queue)
{
struct bfq_queue *bfqq = bic_to_bfqq(bic, is_sync);
if (likely(bfqq && bfqq != &bfqd->oom_bfqq))
return bfqq;
if (new_queue)
*new_queue = true;
if (bfqq)
bfq_put_queue(bfqq);
bfqq = bfq_get_queue(bfqd, bio, is_sync, bic);
bic_set_bfqq(bic, bfqq, is_sync);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
if (split && is_sync) {
if ((bic->was_in_burst_list && bfqd->large_burst) ||
bic->saved_in_large_burst)
bfq_mark_bfqq_in_large_burst(bfqq);
else {
bfq_clear_bfqq_in_large_burst(bfqq);
if (bic->was_in_burst_list)
hlist_add_head(&bfqq->burst_list_node,
&bfqd->burst_list);
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfqq->split_time = jiffies;
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
}
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
return bfqq;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Allocate bfq data structures associated with this request.
*/
static int bfq_get_rq_private(struct request_queue *q, struct request *rq,
struct bio *bio)
{
struct bfq_data *bfqd = q->elevator->elevator_data;
struct bfq_io_cq *bic = icq_to_bic(rq->elv.icq);
const int is_sync = rq_is_sync(rq);
struct bfq_queue *bfqq;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bool new_queue = false;
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
bool split = false;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
spin_lock_irq(&bfqd->lock);
if (!bic)
goto queue_fail;
block, bfq: don't dereference bic before null checking it The call to bfq_check_ioprio_change will dereference bic, however, the null check for bic is after this call. Move the the null check on bic to before the call to avoid any potential null pointer dereference issues. Detected by CoverityScan, CID#1430138 ("Dereference before null check") Signed-off-by: Colin Ian King <colin.king@canonical.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-20 21:07:18 +07:00
bfq_check_ioprio_change(bic, bio);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_bic_update_cgroup(bic, bio);
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfqq = bfq_get_bfqq_handle_split(bfqd, bic, bio, false, is_sync,
&new_queue);
if (likely(!new_queue)) {
/* If the queue was seeky for too long, break it apart. */
if (bfq_bfqq_coop(bfqq) && bfq_bfqq_split_coop(bfqq)) {
bfq_log_bfqq(bfqd, bfqq, "breaking apart bfqq");
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
/* Update bic before losing reference to bfqq */
if (bfq_bfqq_in_large_burst(bfqq))
bic->saved_in_large_burst = true;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
bfqq = bfq_split_bfqq(bic, bfqq);
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
split = true;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
if (!bfqq)
bfqq = bfq_get_bfqq_handle_split(bfqd, bic, bio,
true, is_sync,
NULL);
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
bfqq->allocated++;
bfqq->ref++;
bfq_log_bfqq(bfqd, bfqq, "get_request %p: bfqq %p, %d",
rq, bfqq, bfqq->ref);
rq->elv.priv[0] = bic;
rq->elv.priv[1] = bfqq;
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* If a bfq_queue has only one process reference, it is owned
* by only this bic: we can then set bfqq->bic = bic. in
* addition, if the queue has also just been split, we have to
* resume its state.
*/
if (likely(bfqq != &bfqd->oom_bfqq) && bfqq_process_refs(bfqq) == 1) {
bfqq->bic = bic;
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
if (split) {
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
/*
* The queue has just been split from a shared
* queue: restore the idle window and the
* possible weight raising period.
*/
bfq_bfqq_resume_state(bfqq, bic);
}
}
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
if (unlikely(bfq_bfqq_just_created(bfqq)))
bfq_handle_burst(bfqd, bfqq);
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irq(&bfqd->lock);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return 0;
queue_fail:
spin_unlock_irq(&bfqd->lock);
return 1;
}
static void bfq_idle_slice_timer_body(struct bfq_queue *bfqq)
{
struct bfq_data *bfqd = bfqq->bfqd;
enum bfqq_expiration reason;
unsigned long flags;
spin_lock_irqsave(&bfqd->lock, flags);
bfq_clear_bfqq_wait_request(bfqq);
if (bfqq != bfqd->in_service_queue) {
spin_unlock_irqrestore(&bfqd->lock, flags);
return;
}
if (bfq_bfqq_budget_timeout(bfqq))
/*
* Also here the queue can be safely expired
* for budget timeout without wasting
* guarantees
*/
reason = BFQQE_BUDGET_TIMEOUT;
else if (bfqq->queued[0] == 0 && bfqq->queued[1] == 0)
/*
* The queue may not be empty upon timer expiration,
* because we may not disable the timer when the
* first request of the in-service queue arrives
* during disk idling.
*/
reason = BFQQE_TOO_IDLE;
else
goto schedule_dispatch;
bfq_bfqq_expire(bfqd, bfqq, true, reason);
schedule_dispatch:
block, bfq: remove all get and put of I/O contexts When a bfq queue is set in service and when it is merged, a reference to the I/O context associated with the queue is taken. This reference is then released when the queue is deselected from service or split. More precisely, the release of the reference is postponed to when the scheduler lock is released, to avoid nesting between the scheduler and the I/O-context lock. In fact, such nesting would lead to deadlocks, because of other code paths that take the same locks in the opposite order. This postponing of I/O-context releases does complicate code. This commit addresses these issue by modifying involved operations in such a way to not need to get the above I/O-context references any more. Then it also removes any get and release of these references. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:21 +07:00
spin_unlock_irqrestore(&bfqd->lock, flags);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_schedule_dispatch(bfqd);
}
/*
* Handler of the expiration of the timer running if the in-service queue
* is idling inside its time slice.
*/
static enum hrtimer_restart bfq_idle_slice_timer(struct hrtimer *timer)
{
struct bfq_data *bfqd = container_of(timer, struct bfq_data,
idle_slice_timer);
struct bfq_queue *bfqq = bfqd->in_service_queue;
/*
* Theoretical race here: the in-service queue can be NULL or
* different from the queue that was idling if a new request
* arrives for the current queue and there is a full dispatch
* cycle that changes the in-service queue. This can hardly
* happen, but in the worst case we just expire a queue too
* early.
*/
if (bfqq)
bfq_idle_slice_timer_body(bfqq);
return HRTIMER_NORESTART;
}
static void __bfq_put_async_bfqq(struct bfq_data *bfqd,
struct bfq_queue **bfqq_ptr)
{
struct bfq_queue *bfqq = *bfqq_ptr;
bfq_log(bfqd, "put_async_bfqq: %p", bfqq);
if (bfqq) {
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_bfqq_move(bfqd, bfqq, bfqd->root_group);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_log_bfqq(bfqd, bfqq, "put_async_bfqq: putting %p, %d",
bfqq, bfqq->ref);
bfq_put_queue(bfqq);
*bfqq_ptr = NULL;
}
}
/*
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
* Release all the bfqg references to its async queues. If we are
* deallocating the group these queues may still contain requests, so
* we reparent them to the root cgroup (i.e., the only one that will
* exist for sure until all the requests on a device are gone).
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
*/
block, bfq: split bfq-iosched.c into multiple source files The BFQ I/O scheduler features an optimal fair-queuing (proportional-share) scheduling algorithm, enriched with several mechanisms to boost throughput and reduce latency for interactive and real-time applications. This makes BFQ a large and complex piece of code. This commit addresses this issue by splitting BFQ into three main, independent components, and by moving each component into a separate source file: 1. Main algorithm: handles the interaction with the kernel, and decides which requests to dispatch; it uses the following two further components to achieve its goals. 2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm): computes the schedule, using weights and budgets provided by the above component. 3. cgroups support: handles group operations (creation, destruction, move, ...). Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:48:24 +07:00
void bfq_put_async_queues(struct bfq_data *bfqd, struct bfq_group *bfqg)
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
{
int i, j;
for (i = 0; i < 2; i++)
for (j = 0; j < IOPRIO_BE_NR; j++)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
__bfq_put_async_bfqq(bfqd, &bfqg->async_bfqq[i][j]);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
__bfq_put_async_bfqq(bfqd, &bfqg->async_idle_bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static void bfq_exit_queue(struct elevator_queue *e)
{
struct bfq_data *bfqd = e->elevator_data;
struct bfq_queue *bfqq, *n;
hrtimer_cancel(&bfqd->idle_slice_timer);
spin_lock_irq(&bfqd->lock);
list_for_each_entry_safe(bfqq, n, &bfqd->idle_list, bfqq_list)
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
bfq_deactivate_bfqq(bfqd, bfqq, false, false);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
spin_unlock_irq(&bfqd->lock);
hrtimer_cancel(&bfqd->idle_slice_timer);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
blkcg_deactivate_policy(bfqd->queue, &blkcg_policy_bfq);
#else
spin_lock_irq(&bfqd->lock);
bfq_put_async_queues(bfqd, bfqd->root_group);
kfree(bfqd->root_group);
spin_unlock_irq(&bfqd->lock);
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
kfree(bfqd);
}
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
static void bfq_init_root_group(struct bfq_group *root_group,
struct bfq_data *bfqd)
{
int i;
#ifdef CONFIG_BFQ_GROUP_IOSCHED
root_group->entity.parent = NULL;
root_group->my_entity = NULL;
root_group->bfqd = bfqd;
#endif
block, bfq: add Early Queue Merge (EQM) A set of processes may happen to perform interleaved reads, i.e., read requests whose union would give rise to a sequential read pattern. There are two typical cases: first, processes reading fixed-size chunks of data at a fixed distance from each other; second, processes reading variable-size chunks at variable distances. The latter case occurs for example with QEMU, which splits the I/O generated by a guest into multiple chunks, and lets these chunks be served by a pool of I/O threads, iteratively assigning the next chunk of I/O to the first available thread. CFQ denotes as 'cooperating' a set of processes that are doing interleaved I/O, and when it detects cooperating processes, it merges their queues to obtain a sequential I/O pattern from the union of their I/O requests, and hence boost the throughput. Unfortunately, in the following frequent case, the mechanism implemented in CFQ for detecting cooperating processes and merging their queues is not responsive enough to handle also the fluctuating I/O pattern of the second type of processes. Suppose that one process of the second type issues a request close to the next request to serve of another process of the same type. At that time the two processes would be considered as cooperating. But, if the request issued by the first process is to be merged with some other already-queued request, then, from the moment at which this request arrives, to the moment when CFQ controls whether the two processes are cooperating, the two processes are likely to be already doing I/O in distant zones of the disk surface or device memory. CFQ uses however preemption to get a sequential read pattern out of the read requests performed by the second type of processes too. As a consequence, CFQ uses two different mechanisms to achieve the same goal: boosting the throughput with interleaved I/O. This patch introduces Early Queue Merge (EQM), a unified mechanism to get a sequential read pattern with both types of processes. The main idea is to immediately check whether a newly-arrived request lets some pair of processes become cooperating, both in the case of actual request insertion and, to be responsive with the second type of processes, in the case of request merge. Both types of processes are then handled by just merging their queues. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:16 +07:00
root_group->rq_pos_tree = RB_ROOT;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
for (i = 0; i < BFQ_IOPRIO_CLASSES; i++)
root_group->sched_data.service_tree[i] = BFQ_SERVICE_TREE_INIT;
root_group->sched_data.bfq_class_idle_last_service = jiffies;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
static int bfq_init_queue(struct request_queue *q, struct elevator_type *e)
{
struct bfq_data *bfqd;
struct elevator_queue *eq;
eq = elevator_alloc(q, e);
if (!eq)
return -ENOMEM;
bfqd = kzalloc_node(sizeof(*bfqd), GFP_KERNEL, q->node);
if (!bfqd) {
kobject_put(&eq->kobj);
return -ENOMEM;
}
eq->elevator_data = bfqd;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
spin_lock_irq(q->queue_lock);
q->elevator = eq;
spin_unlock_irq(q->queue_lock);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Our fallback bfqq if bfq_find_alloc_queue() runs into OOM issues.
* Grab a permanent reference to it, so that the normal code flow
* will not attempt to free it.
*/
bfq_init_bfqq(bfqd, &bfqd->oom_bfqq, NULL, 1, 0);
bfqd->oom_bfqq.ref++;
bfqd->oom_bfqq.new_ioprio = BFQ_DEFAULT_QUEUE_IOPRIO;
bfqd->oom_bfqq.new_ioprio_class = IOPRIO_CLASS_BE;
bfqd->oom_bfqq.entity.new_weight =
bfq_ioprio_to_weight(bfqd->oom_bfqq.new_ioprio);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
/* oom_bfqq does not participate to bursts */
bfq_clear_bfqq_just_created(&bfqd->oom_bfqq);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
/*
* Trigger weight initialization, according to ioprio, at the
* oom_bfqq's first activation. The oom_bfqq's ioprio and ioprio
* class won't be changed any more.
*/
bfqd->oom_bfqq.entity.prio_changed = 1;
bfqd->queue = q;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
INIT_LIST_HEAD(&bfqd->dispatch);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
hrtimer_init(&bfqd->idle_slice_timer, CLOCK_MONOTONIC,
HRTIMER_MODE_REL);
bfqd->idle_slice_timer.function = bfq_idle_slice_timer;
block, bfq: reduce idling only in symmetric scenarios A seeky queue (i..e, a queue containing random requests) is assigned a very small device-idling slice, for throughput issues. Unfortunately, given the process associated with a seeky queue, this behavior causes the following problem: if the process, say P, performs sync I/O and has a higher weight than some other processes doing I/O and associated with non-seeky queues, then BFQ may fail to guarantee to P its reserved share of the throughput. The reason is that idling is key for providing service guarantees to processes doing sync I/O [1]. This commit addresses this issue by allowing the device-idling slice to be reduced for a seeky queue only if the scenario happens to be symmetric, i.e., if all the queues are to receive the same share of the throughput. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Riccardo Pizzetti <riccardo.pizzetti@gmail.com> Signed-off-by: Samuele Zecchini <samuele.zecchini92@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:17 +07:00
bfqd->queue_weights_tree = RB_ROOT;
bfqd->group_weights_tree = RB_ROOT;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
INIT_LIST_HEAD(&bfqd->active_list);
INIT_LIST_HEAD(&bfqd->idle_list);
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
INIT_HLIST_HEAD(&bfqd->burst_list);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfqd->hw_tag = -1;
bfqd->bfq_max_budget = bfq_default_max_budget;
bfqd->bfq_fifo_expire[0] = bfq_fifo_expire[0];
bfqd->bfq_fifo_expire[1] = bfq_fifo_expire[1];
bfqd->bfq_back_max = bfq_back_max;
bfqd->bfq_back_penalty = bfq_back_penalty;
bfqd->bfq_slice_idle = bfq_slice_idle;
bfqd->bfq_timeout = bfq_timeout;
bfqd->bfq_requests_within_timer = 120;
block, bfq: handle bursts of queue activations Many popular I/O-intensive services or applications spawn or reactivate many parallel threads/processes during short time intervals. Examples are systemd during boot or git grep. These services or applications benefit mostly from a high throughput: the quicker the I/O generated by their processes is cumulatively served, the sooner the target job of these services or applications gets completed. As a consequence, it is almost always counterproductive to weight-raise any of the queues associated to the processes of these services or applications: in most cases it would just lower the throughput, mainly because weight-raising also implies device idling. To address this issue, an I/O scheduler needs, first, to detect which queues are associated with these services or applications. In this respect, we have that, from the I/O-scheduler standpoint, these services or applications cause bursts of activations, i.e., activations of different queues occurring shortly after each other. However, a shorter burst of activations may be caused also by the start of an application that does not consist in a lot of parallel I/O-bound threads (see the comments on the function bfq_handle_burst for details). In view of these facts, this commit introduces: 1) an heuristic to detect (only) bursts of queue activations caused by services or applications consisting in many parallel I/O-bound threads; 2) the prevention of device idling and weight-raising for the queues belonging to these bursts. Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:20 +07:00
bfqd->bfq_large_burst_thresh = 8;
bfqd->bfq_burst_interval = msecs_to_jiffies(180);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqd->low_latency = true;
/*
* Trade-off between responsiveness and fairness.
*/
bfqd->bfq_wr_coeff = 30;
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqd->bfq_wr_rt_max_time = msecs_to_jiffies(300);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
bfqd->bfq_wr_max_time = 0;
bfqd->bfq_wr_min_idle_time = msecs_to_jiffies(2000);
bfqd->bfq_wr_min_inter_arr_async = msecs_to_jiffies(500);
block, bfq: reduce I/O latency for soft real-time applications To guarantee a low latency also to the I/O requests issued by soft real-time applications, this patch introduces a further heuristic, which weight-raises (in the sense explained in the previous patch) also the queues associated to applications deemed as soft real-time. To be deemed as soft real-time, an application must meet two requirements. First, the application must not require an average bandwidth higher than the approximate bandwidth required to playback or record a compressed high-definition video. Second, the request pattern of the application must be isochronous, i.e., after issuing a request or a batch of requests, the application must stop issuing new requests until all its pending requests have been completed. After that, the application may issue a new batch, and so on. As for the second requirement, it is critical to require also that, after all the pending requests of the application have been completed, an adequate minimum amount of time elapses before the application starts issuing new requests. This prevents also greedy (i.e., I/O-bound) applications from being incorrectly deemed, occasionally, as soft real-time. In fact, if *any amount of time* is fine, then even a greedy application may, paradoxically, meet both the above requirements, if: (1) the application performs random I/O and/or the device is slow, and (2) the CPU load is high. The reason is the following. First, if condition (1) is true, then, during the service of the application, the throughput may be low enough to let the application meet the bandwidth requirement. Second, if condition (2) is true as well, then the application may occasionally behave in an apparently isochronous way, because it may simply stop issuing requests while the CPUs are busy serving other processes. To address this issue, the heuristic leverages the simple fact that greedy applications issue *all* their requests as quickly as they can, whereas soft real-time applications spend some time processing data after each batch of requests is completed. In particular, the heuristic works as follows. First, according to the above isochrony requirement, the heuristic checks whether an application may be soft real-time, thereby giving to the application the opportunity to be deemed as such, only when both the following two conditions happen to hold: 1) the queue associated with the application has expired and is empty, 2) there is no outstanding request of the application. Suppose that both conditions hold at time, say, t_c and that the application issues its next request at time, say, t_i. At time t_c the heuristic computes the next time instant, called soft_rt_next_start in the code, such that, only if t_i >= soft_rt_next_start, then both the next conditions will hold when the application issues its next request: 1) the application will meet the above bandwidth requirement, 2) a given minimum time interval, say Delta, will have elapsed from time t_c (so as to filter out greedy application). The current value of Delta is a little bit higher than the value that we have found, experimentally, to be adequate on a real, general-purpose machine. In particular we had to increase Delta to make the filter quite precise also in slower, embedded systems, and in KVM/QEMU virtual machines (details in the comments on the code). If the application actually issues its next request after time soft_rt_next_start, then its associated queue will be weight-raised for a relatively short time interval. If, during this time interval, the application proves again to meet the bandwidth and isochrony requirements, then the end of the weight-raising period for the queue is moved forward, and so on. Note that an application whose associated queue never happens to be empty when it expires will never have the opportunity to be deemed as soft real-time. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:13 +07:00
bfqd->bfq_wr_max_softrt_rate = 7000; /*
* Approximate rate required
* to playback or record a
* high-definition compressed
* video.
*/
block, bfq: reduce latency during request-pool saturation This patch introduces an heuristic that reduces latency when the I/O-request pool is saturated. This goal is achieved by disabling device idling, for non-weight-raised queues, when there are weight- raised queues with pending or in-flight requests. In fact, as explained in more detail in the comment on the function bfq_bfqq_may_idle(), this reduces the rate at which processes associated with non-weight-raised queues grab requests from the pool, thereby increasing the probability that processes associated with weight-raised queues get a request immediately (or at least soon) when they need one. Along the same line, if there are weight-raised queues, then this patch halves the service rate of async (write) requests for non-weight-raised queues. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:15 +07:00
bfqd->wr_busy_queues = 0;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Begin by assuming, optimistically, that the device is a
* high-speed one, and that its peak rate is equal to 2/3 of
* the highest reference rate.
*/
bfqd->RT_prod = R_fast[blk_queue_nonrot(bfqd->queue)] *
T_fast[blk_queue_nonrot(bfqd->queue)];
bfqd->peak_rate = R_fast[blk_queue_nonrot(bfqd->queue)] * 2 / 3;
bfqd->device_speed = BFQ_BFQD_FAST;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
spin_lock_init(&bfqd->lock);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
/*
* The invocation of the next bfq_create_group_hierarchy
* function is the head of a chain of function calls
* (bfq_create_group_hierarchy->blkcg_activate_policy->
* blk_mq_freeze_queue) that may lead to the invocation of the
* has_work hook function. For this reason,
* bfq_create_group_hierarchy is invoked only after all
* scheduler data has been initialized, apart from the fields
* that can be initialized only after invoking
* bfq_create_group_hierarchy. This, in particular, enables
* has_work to correctly return false. Of course, to avoid
* other inconsistencies, the blk-mq stack must then refrain
* from invoking further scheduler hooks before this init
* function is finished.
*/
bfqd->root_group = bfq_create_group_hierarchy(bfqd, q->node);
if (!bfqd->root_group)
goto out_free;
bfq_init_root_group(bfqd->root_group, bfqd);
bfq_init_entity(&bfqd->oom_bfqq.entity, bfqd->root_group);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return 0;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
out_free:
kfree(bfqd);
kobject_put(&eq->kobj);
return -ENOMEM;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
}
static void bfq_slab_kill(void)
{
kmem_cache_destroy(bfq_pool);
}
static int __init bfq_slab_setup(void)
{
bfq_pool = KMEM_CACHE(bfq_queue, 0);
if (!bfq_pool)
return -ENOMEM;
return 0;
}
static ssize_t bfq_var_show(unsigned int var, char *page)
{
return sprintf(page, "%u\n", var);
}
static ssize_t bfq_var_store(unsigned long *var, const char *page,
size_t count)
{
unsigned long new_val;
int ret = kstrtoul(page, 10, &new_val);
if (ret == 0)
*var = new_val;
return count;
}
#define SHOW_FUNCTION(__FUNC, __VAR, __CONV) \
static ssize_t __FUNC(struct elevator_queue *e, char *page) \
{ \
struct bfq_data *bfqd = e->elevator_data; \
u64 __data = __VAR; \
if (__CONV == 1) \
__data = jiffies_to_msecs(__data); \
else if (__CONV == 2) \
__data = div_u64(__data, NSEC_PER_MSEC); \
return bfq_var_show(__data, (page)); \
}
SHOW_FUNCTION(bfq_fifo_expire_sync_show, bfqd->bfq_fifo_expire[1], 2);
SHOW_FUNCTION(bfq_fifo_expire_async_show, bfqd->bfq_fifo_expire[0], 2);
SHOW_FUNCTION(bfq_back_seek_max_show, bfqd->bfq_back_max, 0);
SHOW_FUNCTION(bfq_back_seek_penalty_show, bfqd->bfq_back_penalty, 0);
SHOW_FUNCTION(bfq_slice_idle_show, bfqd->bfq_slice_idle, 2);
SHOW_FUNCTION(bfq_max_budget_show, bfqd->bfq_user_max_budget, 0);
SHOW_FUNCTION(bfq_timeout_sync_show, bfqd->bfq_timeout, 1);
SHOW_FUNCTION(bfq_strict_guarantees_show, bfqd->strict_guarantees, 0);
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
SHOW_FUNCTION(bfq_low_latency_show, bfqd->low_latency, 0);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
#undef SHOW_FUNCTION
#define USEC_SHOW_FUNCTION(__FUNC, __VAR) \
static ssize_t __FUNC(struct elevator_queue *e, char *page) \
{ \
struct bfq_data *bfqd = e->elevator_data; \
u64 __data = __VAR; \
__data = div_u64(__data, NSEC_PER_USEC); \
return bfq_var_show(__data, (page)); \
}
USEC_SHOW_FUNCTION(bfq_slice_idle_us_show, bfqd->bfq_slice_idle);
#undef USEC_SHOW_FUNCTION
#define STORE_FUNCTION(__FUNC, __PTR, MIN, MAX, __CONV) \
static ssize_t \
__FUNC(struct elevator_queue *e, const char *page, size_t count) \
{ \
struct bfq_data *bfqd = e->elevator_data; \
unsigned long uninitialized_var(__data); \
int ret = bfq_var_store(&__data, (page), count); \
if (__data < (MIN)) \
__data = (MIN); \
else if (__data > (MAX)) \
__data = (MAX); \
if (__CONV == 1) \
*(__PTR) = msecs_to_jiffies(__data); \
else if (__CONV == 2) \
*(__PTR) = (u64)__data * NSEC_PER_MSEC; \
else \
*(__PTR) = __data; \
return ret; \
}
STORE_FUNCTION(bfq_fifo_expire_sync_store, &bfqd->bfq_fifo_expire[1], 1,
INT_MAX, 2);
STORE_FUNCTION(bfq_fifo_expire_async_store, &bfqd->bfq_fifo_expire[0], 1,
INT_MAX, 2);
STORE_FUNCTION(bfq_back_seek_max_store, &bfqd->bfq_back_max, 0, INT_MAX, 0);
STORE_FUNCTION(bfq_back_seek_penalty_store, &bfqd->bfq_back_penalty, 1,
INT_MAX, 0);
STORE_FUNCTION(bfq_slice_idle_store, &bfqd->bfq_slice_idle, 0, INT_MAX, 2);
#undef STORE_FUNCTION
#define USEC_STORE_FUNCTION(__FUNC, __PTR, MIN, MAX) \
static ssize_t __FUNC(struct elevator_queue *e, const char *page, size_t count)\
{ \
struct bfq_data *bfqd = e->elevator_data; \
unsigned long uninitialized_var(__data); \
int ret = bfq_var_store(&__data, (page), count); \
if (__data < (MIN)) \
__data = (MIN); \
else if (__data > (MAX)) \
__data = (MAX); \
*(__PTR) = (u64)__data * NSEC_PER_USEC; \
return ret; \
}
USEC_STORE_FUNCTION(bfq_slice_idle_us_store, &bfqd->bfq_slice_idle, 0,
UINT_MAX);
#undef USEC_STORE_FUNCTION
static ssize_t bfq_max_budget_store(struct elevator_queue *e,
const char *page, size_t count)
{
struct bfq_data *bfqd = e->elevator_data;
unsigned long uninitialized_var(__data);
int ret = bfq_var_store(&__data, (page), count);
if (__data == 0)
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
bfqd->bfq_max_budget = bfq_calc_max_budget(bfqd);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
else {
if (__data > INT_MAX)
__data = INT_MAX;
bfqd->bfq_max_budget = __data;
}
bfqd->bfq_user_max_budget = __data;
return ret;
}
/*
* Leaving this name to preserve name compatibility with cfq
* parameters, but this timeout is used for both sync and async.
*/
static ssize_t bfq_timeout_sync_store(struct elevator_queue *e,
const char *page, size_t count)
{
struct bfq_data *bfqd = e->elevator_data;
unsigned long uninitialized_var(__data);
int ret = bfq_var_store(&__data, (page), count);
if (__data < 1)
__data = 1;
else if (__data > INT_MAX)
__data = INT_MAX;
bfqd->bfq_timeout = msecs_to_jiffies(__data);
if (bfqd->bfq_user_max_budget == 0)
block, bfq: modify the peak-rate estimator Unless the maximum budget B_max that BFQ can assign to a queue is set explicitly by the user, BFQ automatically updates B_max. In particular, BFQ dynamically sets B_max to the number of sectors that can be read, at the current estimated peak rate, during the maximum time, T_max, allowed before a budget timeout occurs. In formulas, if we denote as R_est the estimated peak rate, then B_max = T_max ∗ R_est. Hence, the higher R_est is with respect to the actual device peak rate, the higher the probability that processes incur budget timeouts unjustly is. Besides, a too high value of B_max unnecessarily increases the deviation from an ideal, smooth service. Unfortunately, it is not trivial to estimate the peak rate correctly: because of the presence of sw and hw queues between the scheduler and the device components that finally serve I/O requests, it is hard to say exactly when a given dispatched request is served inside the device, and for how long. As a consequence, it is hard to know precisely at what rate a given set of requests is actually served by the device. On the opposite end, the dispatch time of any request is trivially available, and, from this piece of information, the "dispatch rate" of requests can be immediately computed. So, the idea in the next function is to use what is known, namely request dispatch times (plus, when useful, request completion times), to estimate what is unknown, namely in-device request service rate. The main issue is that, because of the above facts, the rate at which a certain set of requests is dispatched over a certain time interval can vary greatly with respect to the rate at which the same requests are then served. But, since the size of any intermediate queue is limited, and the service scheme is lossless (no request is silently dropped), the following obvious convergence property holds: the number of requests dispatched MUST become closer and closer to the number of requests completed as the observation interval grows. This is the key property used in this new version of the peak-rate estimator. Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:10 +07:00
bfqd->bfq_max_budget = bfq_calc_max_budget(bfqd);
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return ret;
}
static ssize_t bfq_strict_guarantees_store(struct elevator_queue *e,
const char *page, size_t count)
{
struct bfq_data *bfqd = e->elevator_data;
unsigned long uninitialized_var(__data);
int ret = bfq_var_store(&__data, (page), count);
if (__data > 1)
__data = 1;
if (!bfqd->strict_guarantees && __data == 1
&& bfqd->bfq_slice_idle < 8 * NSEC_PER_MSEC)
bfqd->bfq_slice_idle = 8 * NSEC_PER_MSEC;
bfqd->strict_guarantees = __data;
return ret;
}
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
static ssize_t bfq_low_latency_store(struct elevator_queue *e,
const char *page, size_t count)
{
struct bfq_data *bfqd = e->elevator_data;
unsigned long uninitialized_var(__data);
int ret = bfq_var_store(&__data, (page), count);
if (__data > 1)
__data = 1;
if (__data == 0 && bfqd->low_latency != 0)
bfq_end_wr(bfqd);
bfqd->low_latency = __data;
return ret;
}
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
#define BFQ_ATTR(name) \
__ATTR(name, 0644, bfq_##name##_show, bfq_##name##_store)
static struct elv_fs_entry bfq_attrs[] = {
BFQ_ATTR(fifo_expire_sync),
BFQ_ATTR(fifo_expire_async),
BFQ_ATTR(back_seek_max),
BFQ_ATTR(back_seek_penalty),
BFQ_ATTR(slice_idle),
BFQ_ATTR(slice_idle_us),
BFQ_ATTR(max_budget),
BFQ_ATTR(timeout_sync),
BFQ_ATTR(strict_guarantees),
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
BFQ_ATTR(low_latency),
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
__ATTR_NULL
};
static struct elevator_type iosched_bfq_mq = {
.ops.mq = {
.get_rq_priv = bfq_get_rq_private,
.put_rq_priv = bfq_put_rq_private,
.exit_icq = bfq_exit_icq,
.insert_requests = bfq_insert_requests,
.dispatch_request = bfq_dispatch_request,
.next_request = elv_rb_latter_request,
.former_request = elv_rb_former_request,
.allow_merge = bfq_allow_bio_merge,
.bio_merge = bfq_bio_merge,
.request_merge = bfq_request_merge,
.requests_merged = bfq_requests_merged,
.request_merged = bfq_request_merged,
.has_work = bfq_has_work,
.init_sched = bfq_init_queue,
.exit_sched = bfq_exit_queue,
},
.uses_mq = true,
.icq_size = sizeof(struct bfq_io_cq),
.icq_align = __alignof__(struct bfq_io_cq),
.elevator_attrs = bfq_attrs,
.elevator_name = "bfq",
.elevator_owner = THIS_MODULE,
};
static int __init bfq_init(void)
{
int ret;
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
ret = blkcg_policy_register(&blkcg_policy_bfq);
if (ret)
return ret;
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
ret = -ENOMEM;
if (bfq_slab_setup())
goto err_pol_unreg;
block, bfq: improve responsiveness This patch introduces a simple heuristic to load applications quickly, and to perform the I/O requested by interactive applications just as quickly. To this purpose, both a newly-created queue and a queue associated with an interactive application (we explain in a moment how BFQ decides whether the associated application is interactive), receive the following two special treatments: 1) The weight of the queue is raised. 2) The queue unconditionally enjoys device idling when it empties; in fact, if the requests of a queue are sync, then performing device idling for the queue is a necessary condition to guarantee that the queue receives a fraction of the throughput proportional to its weight (see [1] for details). For brevity, we call just weight-raising the combination of these two preferential treatments. For a newly-created queue, weight-raising starts immediately and lasts for a time interval that: 1) depends on the device speed and type (rotational or non-rotational), and 2) is equal to the time needed to load (start up) a large-size application on that device, with cold caches and with no additional workload. Finally, as for guaranteeing a fast execution to interactive, I/O-related tasks (such as opening a file), consider that any interactive application blocks and waits for user input both after starting up and after executing some task. After a while, the user may trigger new operations, after which the application stops again, and so on. Accordingly, the low-latency heuristic weight-raises again a queue in case it becomes backlogged after being idle for a sufficiently long (configurable) time. The weight-raising then lasts for the same time as for a just-created queue. According to our experiments, the combination of this low-latency heuristic and of the improvements described in the previous patch allows BFQ to guarantee a high application responsiveness. [1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O Scheduler", Proceedings of the First Workshop on Mobile System Technologies (MST-2015), May 2015. http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:12 +07:00
/*
* Times to load large popular applications for the typical
* systems installed on the reference devices (see the
* comments before the definitions of the next two
* arrays). Actually, we use slightly slower values, as the
* estimated peak rate tends to be smaller than the actual
* peak rate. The reason for this last fact is that estimates
* are computed over much shorter time intervals than the long
* intervals typically used for benchmarking. Why? First, to
* adapt more quickly to variations. Second, because an I/O
* scheduler cannot rely on a peak-rate-evaluation workload to
* be run for a long time.
*/
T_slow[0] = msecs_to_jiffies(3500); /* actually 4 sec */
T_slow[1] = msecs_to_jiffies(6000); /* actually 6.5 sec */
T_fast[0] = msecs_to_jiffies(7000); /* actually 8 sec */
T_fast[1] = msecs_to_jiffies(2500); /* actually 3 sec */
/*
* Thresholds that determine the switch between speed classes
* (see the comments before the definition of the array
* device_speed_thresh). These thresholds are biased towards
* transitions to the fast class. This is safer than the
* opposite bias. In fact, a wrong transition to the slow
* class results in short weight-raising periods, because the
* speed of the device then tends to be higher that the
* reference peak rate. On the opposite end, a wrong
* transition to the fast class tends to increase
* weight-raising periods, because of the opposite reason.
*/
device_speed_thresh[0] = (4 * R_slow[0]) / 3;
device_speed_thresh[1] = (4 * R_slow[1]) / 3;
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
ret = elv_register(&iosched_bfq_mq);
if (ret)
goto err_pol_unreg;
return 0;
err_pol_unreg:
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
blkcg_policy_unregister(&blkcg_policy_bfq);
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
return ret;
}
static void __exit bfq_exit(void)
{
elv_unregister(&iosched_bfq_mq);
block, bfq: add full hierarchical scheduling and cgroups support Add complete support for full hierarchical scheduling, with a cgroups interface. Full hierarchical scheduling is implemented through the 'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues associated with processes, and groups are represented in general by entities. Given the bfq_queues associated with the processes belonging to a given group, the entities representing these queues are sons of the entity representing the group. At higher levels, if a group, say G, contains other groups, then the entity representing G is the parent entity of the entities representing the groups in G. Hierarchical scheduling is performed as follows: if the timestamps of a leaf entity (i.e., of a bfq_queue) change, and such a change lets the entity become the next-to-serve entity for its parent entity, then the timestamps of the parent entity are recomputed as a function of the budget of its new next-to-serve leaf entity. If the parent entity belongs, in its turn, to a group, and its new timestamps let it become the next-to-serve for its parent entity, then the timestamps of the latter parent entity are recomputed as well, and so on. When a new bfq_queue must be set in service, the reverse path is followed: the next-to-serve highest-level entity is chosen, then its next-to-serve child entity, and so on, until the next-to-serve leaf entity is reached, and the bfq_queue that this entity represents is set in service. Writeback is accounted for on a per-group basis, i.e., for each group, the async I/O requests of the processes of the group are enqueued in a distinct bfq_queue, and the entity associated with this queue is a child of the entity associated with the group. Weights can be assigned explicitly to groups and processes through the cgroups interface, differently from what happens, for single processes, if the cgroups interface is not used (as explained in the description of the previous patch). In particular, since each node has a full scheduler, each group can be assigned its own weight. Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-12 23:23:08 +07:00
#ifdef CONFIG_BFQ_GROUP_IOSCHED
blkcg_policy_unregister(&blkcg_policy_bfq);
#endif
block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler We tag as v0 the version of BFQ containing only BFQ's engine plus hierarchical support. BFQ's engine is introduced by this commit, while hierarchical support is added by next commit. We use the v0 tag to distinguish this minimal version of BFQ from the versions containing also the features and the improvements added by next commits. BFQ-v0 coincides with the version of BFQ submitted a few years ago [1], apart from the introduction of preemption, described below. BFQ is a proportional-share I/O scheduler, whose general structure, plus a lot of code, are borrowed from CFQ. - Each process doing I/O on a device is associated with a weight and a (bfq_)queue. - BFQ grants exclusive access to the device, for a while, to one queue (process) at a time, and implements this service model by associating every queue with a budget, measured in number of sectors. - After a queue is granted access to the device, the budget of the queue is decremented, on each request dispatch, by the size of the request. - The in-service queue is expired, i.e., its service is suspended, only if one of the following events occurs: 1) the queue finishes its budget, 2) the queue empties, 3) a "budget timeout" fires. - The budget timeout prevents processes doing random I/O from holding the device for too long and dramatically reducing throughput. - Actually, as in CFQ, a queue associated with a process issuing sync requests may not be expired immediately when it empties. In contrast, BFQ may idle the device for a short time interval, giving the process the chance to go on being served if it issues a new request in time. Device idling typically boosts the throughput on rotational devices, if processes do synchronous and sequential I/O. In addition, under BFQ, device idling is also instrumental in guaranteeing the desired throughput fraction to processes issuing sync requests (see [2] for details). - With respect to idling for service guarantees, if several processes are competing for the device at the same time, but all processes (and groups, after the following commit) have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. Throughput is thus as high as possible in this common scenario. - Queues are scheduled according to a variant of WF2Q+, named B-WF2Q+, and implemented using an augmented rb-tree to preserve an O(log N) overall complexity. See [2] for more details. B-WF2Q+ is also ready for hierarchical scheduling. However, for a cleaner logical breakdown, the code that enables and completes hierarchical support is provided in the next commit, which focuses exactly on this feature. - B-WF2Q+ guarantees a tight deviation with respect to an ideal, perfectly fair, and smooth service. In particular, B-WF2Q+ guarantees that each queue receives a fraction of the device throughput proportional to its weight, even if the throughput fluctuates, and regardless of: the device parameters, the current workload and the budgets assigned to the queue. - The last, budget-independence, property (although probably counterintuitive in the first place) is definitely beneficial, for the following reasons: - First, with any proportional-share scheduler, the maximum deviation with respect to an ideal service is proportional to the maximum budget (slice) assigned to queues. As a consequence, BFQ can keep this deviation tight not only because of the accurate service of B-WF2Q+, but also because BFQ *does not* need to assign a larger budget to a queue to let the queue receive a higher fraction of the device throughput. - Second, BFQ is free to choose, for every process (queue), the budget that best fits the needs of the process, or best leverages the I/O pattern of the process. In particular, BFQ updates queue budgets with a simple feedback-loop algorithm that allows a high throughput to be achieved, while still providing tight latency guarantees to time-sensitive applications. When the in-service queue expires, this algorithm computes the next budget of the queue so as to: - Let large budgets be eventually assigned to the queues associated with I/O-bound applications performing sequential I/O: in fact, the longer these applications are served once got access to the device, the higher the throughput is. - Let small budgets be eventually assigned to the queues associated with time-sensitive applications (which typically perform sporadic and short I/O), because, the smaller the budget assigned to a queue waiting for service is, the sooner B-WF2Q+ will serve that queue (Subsec 3.3 in [2]). - Weights can be assigned to processes only indirectly, through I/O priorities, and according to the relation: weight = 10 * (IOPRIO_BE_NR - ioprio). The next patch provides, instead, a cgroups interface through which weights can be assigned explicitly. - If several processes are competing for the device at the same time, but all processes and groups have the same weight, then BFQ guarantees the expected throughput distribution without ever idling the device. It uses preemption instead. Throughput is then much higher in this common scenario. - ioprio classes are served in strict priority order, i.e., lower-priority queues are not served as long as there are higher-priority queues. Among queues in the same class, the bandwidth is distributed in proportion to the weight of each queue. A very thin extra bandwidth is however guaranteed to the Idle class, to prevent it from starving. - If the strict_guarantees parameter is set (default: unset), then BFQ - always performs idling when the in-service queue becomes empty; - forces the device to serve one I/O request at a time, by dispatching a new request only if there is no outstanding request. In the presence of differentiated weights or I/O-request sizes, both the above conditions are needed to guarantee that every queue receives its allotted share of the bandwidth (see Documentation/block/bfq-iosched.txt for more details). Setting strict_guarantees may evidently affect throughput. [1] https://lkml.org/lkml/2008/4/1/234 https://lkml.org/lkml/2008/11/11/148 [2] P. Valente and M. Andreolini, "Improving Application Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of the 5th Annual International Systems and Storage Conference (SYSTOR '12), June 2012. Slightly extended version: http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite- results.pdf Signed-off-by: Fabio Checconi <fchecconi@gmail.com> Signed-off-by: Paolo Valente <paolo.valente@linaro.org> Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-19 21:29:02 +07:00
bfq_slab_kill();
}
module_init(bfq_init);
module_exit(bfq_exit);
MODULE_AUTHOR("Paolo Valente");
MODULE_LICENSE("GPL");
MODULE_DESCRIPTION("MQ Budget Fair Queueing I/O Scheduler");
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