linux_dsm_epyc7002/Documentation/block/00-INDEX
Paolo Valente aee69d78de 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 08:29:02 -06:00

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00-INDEX
- This file
bfq-iosched.txt
- BFQ IO scheduler and its tunables
biodoc.txt
- Notes on the Generic Block Layer Rewrite in Linux 2.5
biovecs.txt
- Immutable biovecs and biovec iterators
capability.txt
- Generic Block Device Capability (/sys/block/<device>/capability)
cfq-iosched.txt
- CFQ IO scheduler tunables
cmdline-partition.txt
- how to specify block device partitions on kernel command line
data-integrity.txt
- Block data integrity
deadline-iosched.txt
- Deadline IO scheduler tunables
ioprio.txt
- Block io priorities (in CFQ scheduler)
pr.txt
- Block layer support for Persistent Reservations
null_blk.txt
- Null block for block-layer benchmarking.
queue-sysfs.txt
- Queue's sysfs entries
request.txt
- The members of struct request (in include/linux/blkdev.h)
stat.txt
- Block layer statistics in /sys/block/<device>/stat
switching-sched.txt
- Switching I/O schedulers at runtime
writeback_cache_control.txt
- Control of volatile write back caches