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linux_dsm_epyc7002/block/kyber-iosched.c

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blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
/*
* The Kyber I/O scheduler. Controls latency by throttling queue depths using
* scalable techniques.
*
* Copyright (C) 2017 Facebook
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public
* License v2 as published by the Free Software Foundation.
*
* 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.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <linux/kernel.h>
#include <linux/blkdev.h>
#include <linux/blk-mq.h>
#include <linux/elevator.h>
#include <linux/module.h>
#include <linux/sbitmap.h>
#include "blk.h"
#include "blk-mq.h"
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
#include "blk-mq-debugfs.h"
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
#include "blk-mq-sched.h"
#include "blk-mq-tag.h"
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
#define CREATE_TRACE_POINTS
#include <trace/events/kyber.h>
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
/*
* Scheduling domains: the device is divided into multiple domains based on the
* request type.
*/
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
enum {
KYBER_READ,
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
KYBER_WRITE,
KYBER_DISCARD,
KYBER_OTHER,
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
KYBER_NUM_DOMAINS,
};
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
static const char *kyber_domain_names[] = {
[KYBER_READ] = "READ",
[KYBER_WRITE] = "WRITE",
[KYBER_DISCARD] = "DISCARD",
[KYBER_OTHER] = "OTHER",
};
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
enum {
/*
* In order to prevent starvation of synchronous requests by a flood of
* asynchronous requests, we reserve 25% of requests for synchronous
* operations.
*/
KYBER_ASYNC_PERCENT = 75,
};
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Maximum device-wide depth for each scheduling domain.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Even for fast devices with lots of tags like NVMe, you can saturate the
* device with only a fraction of the maximum possible queue depth. So, we cap
* these to a reasonable value.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
static const unsigned int kyber_depth[] = {
[KYBER_READ] = 256,
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
[KYBER_WRITE] = 128,
[KYBER_DISCARD] = 64,
[KYBER_OTHER] = 16,
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
};
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Default latency targets for each scheduling domain.
*/
static const u64 kyber_latency_targets[] = {
kyber: fix integer overflow of latency targets on 32-bit NSEC_PER_SEC has type long, so 5 * NSEC_PER_SEC is calculated as a long. However, 5 seconds is 5,000,000,000 nanoseconds, which overflows a 32-bit long. Make sure all of the targets are calculated as 64-bit values. Fixes: 6e25cb01ea20 ("kyber: implement improved heuristics") Reported-by: Stephen Rothwell <sfr@canb.auug.org.au> Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 23:22:50 +07:00
[KYBER_READ] = 2ULL * NSEC_PER_MSEC,
[KYBER_WRITE] = 10ULL * NSEC_PER_MSEC,
[KYBER_DISCARD] = 5ULL * NSEC_PER_SEC,
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
};
/*
* Batch size (number of requests we'll dispatch in a row) for each scheduling
* domain.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
static const unsigned int kyber_batch_size[] = {
[KYBER_READ] = 16,
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
[KYBER_WRITE] = 8,
[KYBER_DISCARD] = 1,
[KYBER_OTHER] = 1,
};
/*
* Requests latencies are recorded in a histogram with buckets defined relative
* to the target latency:
*
* <= 1/4 * target latency
* <= 1/2 * target latency
* <= 3/4 * target latency
* <= target latency
* <= 1 1/4 * target latency
* <= 1 1/2 * target latency
* <= 1 3/4 * target latency
* > 1 3/4 * target latency
*/
enum {
/*
* The width of the latency histogram buckets is
* 1 / (1 << KYBER_LATENCY_SHIFT) * target latency.
*/
KYBER_LATENCY_SHIFT = 2,
/*
* The first (1 << KYBER_LATENCY_SHIFT) buckets are <= target latency,
* thus, "good".
*/
KYBER_GOOD_BUCKETS = 1 << KYBER_LATENCY_SHIFT,
/* There are also (1 << KYBER_LATENCY_SHIFT) "bad" buckets. */
KYBER_LATENCY_BUCKETS = 2 << KYBER_LATENCY_SHIFT,
};
/*
* We measure both the total latency and the I/O latency (i.e., latency after
* submitting to the device).
*/
enum {
KYBER_TOTAL_LATENCY,
KYBER_IO_LATENCY,
};
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
static const char *kyber_latency_type_names[] = {
[KYBER_TOTAL_LATENCY] = "total",
[KYBER_IO_LATENCY] = "I/O",
};
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
/*
* Per-cpu latency histograms: total latency and I/O latency for each scheduling
* domain except for KYBER_OTHER.
*/
struct kyber_cpu_latency {
atomic_t buckets[KYBER_OTHER][2][KYBER_LATENCY_BUCKETS];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
};
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
/*
* There is a same mapping between ctx & hctx and kcq & khd,
* we use request->mq_ctx->index_hw to index the kcq in khd.
*/
struct kyber_ctx_queue {
/*
* Used to ensure operations on rq_list and kcq_map to be an atmoic one.
* Also protect the rqs on rq_list when merge.
*/
spinlock_t lock;
struct list_head rq_list[KYBER_NUM_DOMAINS];
} ____cacheline_aligned_in_smp;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
struct kyber_queue_data {
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
struct request_queue *q;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Each scheduling domain has a limited number of in-flight requests
* device-wide, limited by these tokens.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
struct sbitmap_queue domain_tokens[KYBER_NUM_DOMAINS];
/*
* Async request percentage, converted to per-word depth for
* sbitmap_get_shallow().
*/
unsigned int async_depth;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
struct kyber_cpu_latency __percpu *cpu_latency;
/* Timer for stats aggregation and adjusting domain tokens. */
struct timer_list timer;
unsigned int latency_buckets[KYBER_OTHER][2][KYBER_LATENCY_BUCKETS];
unsigned long latency_timeout[KYBER_OTHER];
int domain_p99[KYBER_OTHER];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
/* Target latencies in nanoseconds. */
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
u64 latency_targets[KYBER_OTHER];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
};
struct kyber_hctx_data {
spinlock_t lock;
struct list_head rqs[KYBER_NUM_DOMAINS];
unsigned int cur_domain;
unsigned int batching;
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
struct kyber_ctx_queue *kcqs;
struct sbitmap kcq_map[KYBER_NUM_DOMAINS];
sched/wait: Rename wait_queue_t => wait_queue_entry_t Rename: wait_queue_t => wait_queue_entry_t 'wait_queue_t' was always a slight misnomer: its name implies that it's a "queue", but in reality it's a queue *entry*. The 'real' queue is the wait queue head, which had to carry the name. Start sorting this out by renaming it to 'wait_queue_entry_t'. This also allows the real structure name 'struct __wait_queue' to lose its double underscore and become 'struct wait_queue_entry', which is the more canonical nomenclature for such data types. Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:13 +07:00
wait_queue_entry_t domain_wait[KYBER_NUM_DOMAINS];
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
struct sbq_wait_state *domain_ws[KYBER_NUM_DOMAINS];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
atomic_t wait_index[KYBER_NUM_DOMAINS];
};
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
static int kyber_domain_wake(wait_queue_entry_t *wait, unsigned mode, int flags,
void *key);
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
static unsigned int kyber_sched_domain(unsigned int op)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
switch (op & REQ_OP_MASK) {
case REQ_OP_READ:
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return KYBER_READ;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
case REQ_OP_WRITE:
return KYBER_WRITE;
case REQ_OP_DISCARD:
return KYBER_DISCARD;
default:
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return KYBER_OTHER;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static void flush_latency_buckets(struct kyber_queue_data *kqd,
struct kyber_cpu_latency *cpu_latency,
unsigned int sched_domain, unsigned int type)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
unsigned int *buckets = kqd->latency_buckets[sched_domain][type];
atomic_t *cpu_buckets = cpu_latency->buckets[sched_domain][type];
unsigned int bucket;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
for (bucket = 0; bucket < KYBER_LATENCY_BUCKETS; bucket++)
buckets[bucket] += atomic_xchg(&cpu_buckets[bucket], 0);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Calculate the histogram bucket with the given percentile rank, or -1 if there
* aren't enough samples yet.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static int calculate_percentile(struct kyber_queue_data *kqd,
unsigned int sched_domain, unsigned int type,
unsigned int percentile)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
unsigned int *buckets = kqd->latency_buckets[sched_domain][type];
unsigned int bucket, samples = 0, percentile_samples;
for (bucket = 0; bucket < KYBER_LATENCY_BUCKETS; bucket++)
samples += buckets[bucket];
if (!samples)
return -1;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* We do the calculation once we have 500 samples or one second passes
* since the first sample was recorded, whichever comes first.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
if (!kqd->latency_timeout[sched_domain])
kqd->latency_timeout[sched_domain] = max(jiffies + HZ, 1UL);
if (samples < 500 &&
time_is_after_jiffies(kqd->latency_timeout[sched_domain])) {
return -1;
}
kqd->latency_timeout[sched_domain] = 0;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
percentile_samples = DIV_ROUND_UP(samples * percentile, 100);
for (bucket = 0; bucket < KYBER_LATENCY_BUCKETS - 1; bucket++) {
if (buckets[bucket] >= percentile_samples)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
break;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
percentile_samples -= buckets[bucket];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
memset(buckets, 0, sizeof(kqd->latency_buckets[sched_domain][type]));
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
trace_kyber_latency(kqd->q, kyber_domain_names[sched_domain],
kyber_latency_type_names[type], percentile,
bucket + 1, 1 << KYBER_LATENCY_SHIFT, samples);
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
return bucket;
}
static void kyber_resize_domain(struct kyber_queue_data *kqd,
unsigned int sched_domain, unsigned int depth)
{
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
depth = clamp(depth, 1U, kyber_depth[sched_domain]);
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
if (depth != kqd->domain_tokens[sched_domain].sb.depth) {
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
sbitmap_queue_resize(&kqd->domain_tokens[sched_domain], depth);
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
trace_kyber_adjust(kqd->q, kyber_domain_names[sched_domain],
depth);
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static void kyber_timer_fn(struct timer_list *t)
{
struct kyber_queue_data *kqd = from_timer(kqd, t, timer);
unsigned int sched_domain;
int cpu;
bool bad = false;
/* Sum all of the per-cpu latency histograms. */
for_each_online_cpu(cpu) {
struct kyber_cpu_latency *cpu_latency;
cpu_latency = per_cpu_ptr(kqd->cpu_latency, cpu);
for (sched_domain = 0; sched_domain < KYBER_OTHER; sched_domain++) {
flush_latency_buckets(kqd, cpu_latency, sched_domain,
KYBER_TOTAL_LATENCY);
flush_latency_buckets(kqd, cpu_latency, sched_domain,
KYBER_IO_LATENCY);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
/*
* Check if any domains have a high I/O latency, which might indicate
* congestion in the device. Note that we use the p90; we don't want to
* be too sensitive to outliers here.
*/
for (sched_domain = 0; sched_domain < KYBER_OTHER; sched_domain++) {
int p90;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
p90 = calculate_percentile(kqd, sched_domain, KYBER_IO_LATENCY,
90);
if (p90 >= KYBER_GOOD_BUCKETS)
bad = true;
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
/*
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
* Adjust the scheduling domain depths. If we determined that there was
* congestion, we throttle all domains with good latencies. Either way,
* we ease up on throttling domains with bad latencies.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
for (sched_domain = 0; sched_domain < KYBER_OTHER; sched_domain++) {
unsigned int orig_depth, depth;
int p99;
p99 = calculate_percentile(kqd, sched_domain,
KYBER_TOTAL_LATENCY, 99);
/*
* This is kind of subtle: different domains will not
* necessarily have enough samples to calculate the latency
* percentiles during the same window, so we have to remember
* the p99 for the next time we observe congestion; once we do,
* we don't want to throttle again until we get more data, so we
* reset it to -1.
*/
if (bad) {
if (p99 < 0)
p99 = kqd->domain_p99[sched_domain];
kqd->domain_p99[sched_domain] = -1;
} else if (p99 >= 0) {
kqd->domain_p99[sched_domain] = p99;
}
if (p99 < 0)
continue;
/*
* If this domain has bad latency, throttle less. Otherwise,
* throttle more iff we determined that there is congestion.
*
* The new depth is scaled linearly with the p99 latency vs the
* latency target. E.g., if the p99 is 3/4 of the target, then
* we throttle down to 3/4 of the current depth, and if the p99
* is 2x the target, then we double the depth.
*/
if (bad || p99 >= KYBER_GOOD_BUCKETS) {
orig_depth = kqd->domain_tokens[sched_domain].sb.depth;
depth = (orig_depth * (p99 + 1)) >> KYBER_LATENCY_SHIFT;
kyber_resize_domain(kqd, sched_domain, depth);
}
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static unsigned int kyber_sched_tags_shift(struct request_queue *q)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
/*
* All of the hardware queues have the same depth, so we can just grab
* the shift of the first one.
*/
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
return q->queue_hw_ctx[0]->sched_tags->bitmap_tags.sb.shift;
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
static struct kyber_queue_data *kyber_queue_data_alloc(struct request_queue *q)
{
struct kyber_queue_data *kqd;
unsigned int shift;
int ret = -ENOMEM;
int i;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
kqd = kzalloc_node(sizeof(*kqd), GFP_KERNEL, q->node);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
if (!kqd)
goto err;
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
kqd->q = q;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
kqd->cpu_latency = alloc_percpu_gfp(struct kyber_cpu_latency,
GFP_KERNEL | __GFP_ZERO);
if (!kqd->cpu_latency)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
goto err_kqd;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
timer_setup(&kqd->timer, kyber_timer_fn, 0);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
for (i = 0; i < KYBER_NUM_DOMAINS; i++) {
WARN_ON(!kyber_depth[i]);
WARN_ON(!kyber_batch_size[i]);
ret = sbitmap_queue_init_node(&kqd->domain_tokens[i],
kyber: don't make domain token sbitmap larger than necessary The domain token sbitmaps are currently initialized to the device queue depth or 256, whichever is larger, and immediately resized to the maximum depth for that domain (256, 128, or 64 for read, write, and other, respectively). The sbitmap is never resized larger than that, so it's unnecessary to allocate a bitmap larger than the maximum depth. Let's just allocate it to the maximum depth to begin with. This will use marginally less memory, and more importantly, give us a more appropriate number of bits per sbitmap word. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:53 +07:00
kyber_depth[i], -1, false,
GFP_KERNEL, q->node);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
if (ret) {
while (--i >= 0)
sbitmap_queue_free(&kqd->domain_tokens[i]);
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
goto err_buckets;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
for (i = 0; i < KYBER_OTHER; i++) {
kqd->domain_p99[i] = -1;
kqd->latency_targets[i] = kyber_latency_targets[i];
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
shift = kyber_sched_tags_shift(q);
kqd->async_depth = (1U << shift) * KYBER_ASYNC_PERCENT / 100U;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return kqd;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
err_buckets:
free_percpu(kqd->cpu_latency);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
err_kqd:
kfree(kqd);
err:
return ERR_PTR(ret);
}
static int kyber_init_sched(struct request_queue *q, struct elevator_type *e)
{
struct kyber_queue_data *kqd;
struct elevator_queue *eq;
eq = elevator_alloc(q, e);
if (!eq)
return -ENOMEM;
kqd = kyber_queue_data_alloc(q);
if (IS_ERR(kqd)) {
kobject_put(&eq->kobj);
return PTR_ERR(kqd);
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
blk_stat_enable_accounting(q);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
eq->elevator_data = kqd;
q->elevator = eq;
return 0;
}
static void kyber_exit_sched(struct elevator_queue *e)
{
struct kyber_queue_data *kqd = e->elevator_data;
int i;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
del_timer_sync(&kqd->timer);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
for (i = 0; i < KYBER_NUM_DOMAINS; i++)
sbitmap_queue_free(&kqd->domain_tokens[i]);
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
free_percpu(kqd->cpu_latency);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kfree(kqd);
}
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
static void kyber_ctx_queue_init(struct kyber_ctx_queue *kcq)
{
unsigned int i;
spin_lock_init(&kcq->lock);
for (i = 0; i < KYBER_NUM_DOMAINS; i++)
INIT_LIST_HEAD(&kcq->rq_list[i]);
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
static int kyber_init_hctx(struct blk_mq_hw_ctx *hctx, unsigned int hctx_idx)
{
kyber-iosched: update shallow depth when setting up hardware queue We don't expect the async depth to be smaller than the wake batch count for sbitmap, but just in case, inform sbitmap of what shallow depth kyber may use. Acked-by: Paolo Valente <paolo.valente@linaro.org> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-10 02:55:14 +07:00
struct kyber_queue_data *kqd = hctx->queue->elevator->elevator_data;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
struct kyber_hctx_data *khd;
int i;
khd = kmalloc_node(sizeof(*khd), GFP_KERNEL, hctx->numa_node);
if (!khd)
return -ENOMEM;
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
khd->kcqs = kmalloc_array_node(hctx->nr_ctx,
sizeof(struct kyber_ctx_queue),
GFP_KERNEL, hctx->numa_node);
if (!khd->kcqs)
goto err_khd;
for (i = 0; i < hctx->nr_ctx; i++)
kyber_ctx_queue_init(&khd->kcqs[i]);
for (i = 0; i < KYBER_NUM_DOMAINS; i++) {
if (sbitmap_init_node(&khd->kcq_map[i], hctx->nr_ctx,
ilog2(8), GFP_KERNEL, hctx->numa_node)) {
while (--i >= 0)
sbitmap_free(&khd->kcq_map[i]);
goto err_kcqs;
}
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
spin_lock_init(&khd->lock);
for (i = 0; i < KYBER_NUM_DOMAINS; i++) {
INIT_LIST_HEAD(&khd->rqs[i]);
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
init_waitqueue_func_entry(&khd->domain_wait[i],
kyber_domain_wake);
khd->domain_wait[i].private = hctx;
sched/wait: Disambiguate wq_entry->task_list and wq_head->task_list naming So I've noticed a number of instances where it was not obvious from the code whether ->task_list was for a wait-queue head or a wait-queue entry. Furthermore, there's a number of wait-queue users where the lists are not for 'tasks' but other entities (poll tables, etc.), in which case the 'task_list' name is actively confusing. To clear this all up, name the wait-queue head and entry list structure fields unambiguously: struct wait_queue_head::task_list => ::head struct wait_queue_entry::task_list => ::entry For example, this code: rqw->wait.task_list.next != &wait->task_list ... is was pretty unclear (to me) what it's doing, while now it's written this way: rqw->wait.head.next != &wait->entry ... which makes it pretty clear that we are iterating a list until we see the head. Other examples are: list_for_each_entry_safe(pos, next, &x->task_list, task_list) { list_for_each_entry(wq, &fence->wait.task_list, task_list) { ... where it's unclear (to me) what we are iterating, and during review it's hard to tell whether it's trying to walk a wait-queue entry (which would be a bug), while now it's written as: list_for_each_entry_safe(pos, next, &x->head, entry) { list_for_each_entry(wq, &fence->wait.head, entry) { Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:46 +07:00
INIT_LIST_HEAD(&khd->domain_wait[i].entry);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
atomic_set(&khd->wait_index[i], 0);
}
khd->cur_domain = 0;
khd->batching = 0;
hctx->sched_data = khd;
kyber-iosched: update shallow depth when setting up hardware queue We don't expect the async depth to be smaller than the wake batch count for sbitmap, but just in case, inform sbitmap of what shallow depth kyber may use. Acked-by: Paolo Valente <paolo.valente@linaro.org> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-10 02:55:14 +07:00
sbitmap_queue_min_shallow_depth(&hctx->sched_tags->bitmap_tags,
kqd->async_depth);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return 0;
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
err_kcqs:
kfree(khd->kcqs);
err_khd:
kfree(khd);
return -ENOMEM;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
static void kyber_exit_hctx(struct blk_mq_hw_ctx *hctx, unsigned int hctx_idx)
{
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
struct kyber_hctx_data *khd = hctx->sched_data;
int i;
for (i = 0; i < KYBER_NUM_DOMAINS; i++)
sbitmap_free(&khd->kcq_map[i]);
kfree(khd->kcqs);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kfree(hctx->sched_data);
}
static int rq_get_domain_token(struct request *rq)
{
return (long)rq->elv.priv[0];
}
static void rq_set_domain_token(struct request *rq, int token)
{
rq->elv.priv[0] = (void *)(long)token;
}
static void rq_clear_domain_token(struct kyber_queue_data *kqd,
struct request *rq)
{
unsigned int sched_domain;
int nr;
nr = rq_get_domain_token(rq);
if (nr != -1) {
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
sched_domain = kyber_sched_domain(rq->cmd_flags);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
sbitmap_queue_clear(&kqd->domain_tokens[sched_domain], nr,
rq->mq_ctx->cpu);
}
}
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
static void kyber_limit_depth(unsigned int op, struct blk_mq_alloc_data *data)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
/*
* We use the scheduler tags as per-hardware queue queueing tokens.
* Async requests can be limited at this stage.
*/
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
if (!op_is_sync(op)) {
struct kyber_queue_data *kqd = data->q->elevator->elevator_data;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
data->shallow_depth = kqd->async_depth;
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
}
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
static bool kyber_bio_merge(struct blk_mq_hw_ctx *hctx, struct bio *bio)
{
struct kyber_hctx_data *khd = hctx->sched_data;
struct blk_mq_ctx *ctx = blk_mq_get_ctx(hctx->queue);
struct kyber_ctx_queue *kcq = &khd->kcqs[ctx->index_hw];
unsigned int sched_domain = kyber_sched_domain(bio->bi_opf);
struct list_head *rq_list = &kcq->rq_list[sched_domain];
bool merged;
spin_lock(&kcq->lock);
merged = blk_mq_bio_list_merge(hctx->queue, rq_list, bio);
spin_unlock(&kcq->lock);
blk_mq_put_ctx(ctx);
return merged;
}
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
static void kyber_prepare_request(struct request *rq, struct bio *bio)
{
rq_set_domain_token(rq, -1);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
static void kyber_insert_requests(struct blk_mq_hw_ctx *hctx,
struct list_head *rq_list, bool at_head)
{
struct kyber_hctx_data *khd = hctx->sched_data;
struct request *rq, *next;
list_for_each_entry_safe(rq, next, rq_list, queuelist) {
unsigned int sched_domain = kyber_sched_domain(rq->cmd_flags);
struct kyber_ctx_queue *kcq = &khd->kcqs[rq->mq_ctx->index_hw];
struct list_head *head = &kcq->rq_list[sched_domain];
spin_lock(&kcq->lock);
if (at_head)
list_move(&rq->queuelist, head);
else
list_move_tail(&rq->queuelist, head);
sbitmap_set_bit(&khd->kcq_map[sched_domain],
rq->mq_ctx->index_hw);
blk_mq_sched_request_inserted(rq);
spin_unlock(&kcq->lock);
}
}
blk-mq-sched: unify request finished methods No need to have two different callouts of bfq vs kyber. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:21 +07:00
static void kyber_finish_request(struct request *rq)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
blk-mq-sched: unify request finished methods No need to have two different callouts of bfq vs kyber. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:21 +07:00
struct kyber_queue_data *kqd = rq->q->elevator->elevator_data;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
rq_clear_domain_token(kqd, rq);
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static void add_latency_sample(struct kyber_cpu_latency *cpu_latency,
unsigned int sched_domain, unsigned int type,
u64 target, u64 latency)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
unsigned int bucket;
u64 divisor;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
if (latency > 0) {
divisor = max_t(u64, target >> KYBER_LATENCY_SHIFT, 1);
bucket = min_t(unsigned int, div64_u64(latency - 1, divisor),
KYBER_LATENCY_BUCKETS - 1);
} else {
bucket = 0;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
atomic_inc(&cpu_latency->buckets[sched_domain][type][bucket]);
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static void kyber_completed_request(struct request *rq, u64 now)
{
struct kyber_queue_data *kqd = rq->q->elevator->elevator_data;
struct kyber_cpu_latency *cpu_latency;
unsigned int sched_domain;
u64 target;
sched_domain = kyber_sched_domain(rq->cmd_flags);
if (sched_domain == KYBER_OTHER)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return;
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
cpu_latency = get_cpu_ptr(kqd->cpu_latency);
target = kqd->latency_targets[sched_domain];
add_latency_sample(cpu_latency, sched_domain, KYBER_TOTAL_LATENCY,
target, now - rq->start_time_ns);
add_latency_sample(cpu_latency, sched_domain, KYBER_IO_LATENCY, target,
now - rq->io_start_time_ns);
put_cpu_ptr(kqd->cpu_latency);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
timer_reduce(&kqd->timer, jiffies + HZ / 10);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
struct flush_kcq_data {
struct kyber_hctx_data *khd;
unsigned int sched_domain;
struct list_head *list;
};
static bool flush_busy_kcq(struct sbitmap *sb, unsigned int bitnr, void *data)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
struct flush_kcq_data *flush_data = data;
struct kyber_ctx_queue *kcq = &flush_data->khd->kcqs[bitnr];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
spin_lock(&kcq->lock);
list_splice_tail_init(&kcq->rq_list[flush_data->sched_domain],
flush_data->list);
sbitmap_clear_bit(sb, bitnr);
spin_unlock(&kcq->lock);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
return true;
}
static void kyber_flush_busy_kcqs(struct kyber_hctx_data *khd,
unsigned int sched_domain,
struct list_head *list)
{
struct flush_kcq_data data = {
.khd = khd,
.sched_domain = sched_domain,
.list = list,
};
sbitmap_for_each_set(&khd->kcq_map[sched_domain],
flush_busy_kcq, &data);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
sched/wait: Rename wait_queue_t => wait_queue_entry_t Rename: wait_queue_t => wait_queue_entry_t 'wait_queue_t' was always a slight misnomer: its name implies that it's a "queue", but in reality it's a queue *entry*. The 'real' queue is the wait queue head, which had to carry the name. Start sorting this out by renaming it to 'wait_queue_entry_t'. This also allows the real structure name 'struct __wait_queue' to lose its double underscore and become 'struct wait_queue_entry', which is the more canonical nomenclature for such data types. Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:13 +07:00
static int kyber_domain_wake(wait_queue_entry_t *wait, unsigned mode, int flags,
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
void *key)
{
struct blk_mq_hw_ctx *hctx = READ_ONCE(wait->private);
sched/wait: Disambiguate wq_entry->task_list and wq_head->task_list naming So I've noticed a number of instances where it was not obvious from the code whether ->task_list was for a wait-queue head or a wait-queue entry. Furthermore, there's a number of wait-queue users where the lists are not for 'tasks' but other entities (poll tables, etc.), in which case the 'task_list' name is actively confusing. To clear this all up, name the wait-queue head and entry list structure fields unambiguously: struct wait_queue_head::task_list => ::head struct wait_queue_entry::task_list => ::entry For example, this code: rqw->wait.task_list.next != &wait->task_list ... is was pretty unclear (to me) what it's doing, while now it's written this way: rqw->wait.head.next != &wait->entry ... which makes it pretty clear that we are iterating a list until we see the head. Other examples are: list_for_each_entry_safe(pos, next, &x->task_list, task_list) { list_for_each_entry(wq, &fence->wait.task_list, task_list) { ... where it's unclear (to me) what we are iterating, and during review it's hard to tell whether it's trying to walk a wait-queue entry (which would be a bug), while now it's written as: list_for_each_entry_safe(pos, next, &x->head, entry) { list_for_each_entry(wq, &fence->wait.head, entry) { Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:46 +07:00
list_del_init(&wait->entry);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
blk_mq_run_hw_queue(hctx, true);
return 1;
}
static int kyber_get_domain_token(struct kyber_queue_data *kqd,
struct kyber_hctx_data *khd,
struct blk_mq_hw_ctx *hctx)
{
unsigned int sched_domain = khd->cur_domain;
struct sbitmap_queue *domain_tokens = &kqd->domain_tokens[sched_domain];
sched/wait: Rename wait_queue_t => wait_queue_entry_t Rename: wait_queue_t => wait_queue_entry_t 'wait_queue_t' was always a slight misnomer: its name implies that it's a "queue", but in reality it's a queue *entry*. The 'real' queue is the wait queue head, which had to carry the name. Start sorting this out by renaming it to 'wait_queue_entry_t'. This also allows the real structure name 'struct __wait_queue' to lose its double underscore and become 'struct wait_queue_entry', which is the more canonical nomenclature for such data types. Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:13 +07:00
wait_queue_entry_t *wait = &khd->domain_wait[sched_domain];
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
struct sbq_wait_state *ws;
int nr;
nr = __sbitmap_queue_get(domain_tokens);
/*
* If we failed to get a domain token, make sure the hardware queue is
* run when one becomes available. Note that this is serialized on
* khd->lock, but we still need to be careful about the waker.
*/
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
if (nr < 0 && list_empty_careful(&wait->entry)) {
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
ws = sbq_wait_ptr(domain_tokens,
&khd->wait_index[sched_domain]);
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
khd->domain_ws[sched_domain] = ws;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
add_wait_queue(&ws->wait, wait);
/*
* Try again in case a token was freed before we got on the wait
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
* queue.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
nr = __sbitmap_queue_get(domain_tokens);
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
}
kyber: fix hang on domain token wait queue When we're getting a domain token, if we fail to get a token on our first attempt, we put the current hardware queue on a wait queue and then try again just in case a token was freed after our initial attempt but before we got on the wait queue. If this second attempt succeeds, we currently leave the hardware queue on the wait queue. Usually this is okay; we'll just run the hardware queue one extra time when another token is freed. However, if the hardware queue doesn't have any other requests waiting, then when it it gets the extra wakeup, it won't have anything to free and therefore won't wake up any other hardware queues. If tokens are limited, then we won't make forward progress and the device will hang. Reported-by: Bin Zha <zhabin.zb@alibaba-inc.com> Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-10-12 00:39:15 +07:00
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
/*
* If we got a token while we were on the wait queue, remove ourselves
* from the wait queue to ensure that all wake ups make forward
* progress. It's possible that the waker already deleted the entry
* between the !list_empty_careful() check and us grabbing the lock, but
* list_del_init() is okay with that.
*/
if (nr >= 0 && !list_empty_careful(&wait->entry)) {
ws = khd->domain_ws[sched_domain];
spin_lock_irq(&ws->wait.lock);
list_del_init(&wait->entry);
spin_unlock_irq(&ws->wait.lock);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: fix another domain token wait queue hang Commit 8cf466602028 ("kyber: fix hang on domain token wait queue") fixed a hang caused by leaving wait entries on the domain token wait queue after the __sbitmap_queue_get() retry succeeded, making that wait entry a "dud" which won't in turn wake more entries up. However, we can also get a dud entry if kyber_get_domain_token() fails once but is then called again and succeeds. This can happen if the hardware queue is rerun for some other reason, or, more likely, kyber_dispatch_request() tries the same domain twice. The fix is to remove our entry from the wait queue whenever we successfully get a token. The only complication is that we might be on one of many wait queues in the struct sbitmap_queue, but that's easily fixed by remembering which wait queue we were put on. While we're here, only initialize the wait queue entry once instead of on every wait, and use spin_lock_irq() instead of spin_lock_irqsave(), since this is always called from process context with irqs enabled. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-12-06 13:57:43 +07:00
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return nr;
}
static struct request *
kyber_dispatch_cur_domain(struct kyber_queue_data *kqd,
struct kyber_hctx_data *khd,
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
struct blk_mq_hw_ctx *hctx)
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{
struct list_head *rqs;
struct request *rq;
int nr;
rqs = &khd->rqs[khd->cur_domain];
/*
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
* If we already have a flushed request, then we just need to get a
* token for it. Otherwise, if there are pending requests in the kcqs,
* flush the kcqs, but only if we can get a token. If not, we should
* leave the requests in the kcqs so that they can be merged. Note that
* khd->lock serializes the flushes, so if we observed any bit set in
* the kcq_map, we will always get a request.
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
*/
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
rq = list_first_entry_or_null(rqs, struct request, queuelist);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
if (rq) {
nr = kyber_get_domain_token(kqd, khd, hctx);
if (nr >= 0) {
khd->batching++;
rq_set_domain_token(rq, nr);
list_del_init(&rq->queuelist);
return rq;
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
} else {
trace_kyber_throttled(kqd->q,
kyber_domain_names[khd->cur_domain]);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
} else if (sbitmap_any_bit_set(&khd->kcq_map[khd->cur_domain])) {
nr = kyber_get_domain_token(kqd, khd, hctx);
if (nr >= 0) {
kyber_flush_busy_kcqs(khd, khd->cur_domain, rqs);
rq = list_first_entry(rqs, struct request, queuelist);
khd->batching++;
rq_set_domain_token(rq, nr);
list_del_init(&rq->queuelist);
return rq;
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
} else {
trace_kyber_throttled(kqd->q,
kyber_domain_names[khd->cur_domain]);
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
}
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
/* There were either no pending requests or no tokens. */
return NULL;
}
static struct request *kyber_dispatch_request(struct blk_mq_hw_ctx *hctx)
{
struct kyber_queue_data *kqd = hctx->queue->elevator->elevator_data;
struct kyber_hctx_data *khd = hctx->sched_data;
struct request *rq;
int i;
spin_lock(&khd->lock);
/*
* First, if we are still entitled to batch, try to dispatch a request
* from the batch.
*/
if (khd->batching < kyber_batch_size[khd->cur_domain]) {
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
rq = kyber_dispatch_cur_domain(kqd, khd, hctx);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
if (rq)
goto out;
}
/*
* Either,
* 1. We were no longer entitled to a batch.
* 2. The domain we were batching didn't have any requests.
* 3. The domain we were batching was out of tokens.
*
* Start another batch. Note that this wraps back around to the original
* domain if no other domains have requests or tokens.
*/
khd->batching = 0;
for (i = 0; i < KYBER_NUM_DOMAINS; i++) {
if (khd->cur_domain == KYBER_NUM_DOMAINS - 1)
khd->cur_domain = 0;
else
khd->cur_domain++;
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
rq = kyber_dispatch_cur_domain(kqd, khd, hctx);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
if (rq)
goto out;
}
rq = NULL;
out:
spin_unlock(&khd->lock);
return rq;
}
static bool kyber_has_work(struct blk_mq_hw_ctx *hctx)
{
struct kyber_hctx_data *khd = hctx->sched_data;
int i;
for (i = 0; i < KYBER_NUM_DOMAINS; i++) {
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
if (!list_empty_careful(&khd->rqs[i]) ||
sbitmap_any_bit_set(&khd->kcq_map[i]))
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
return true;
}
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
return false;
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
#define KYBER_LAT_SHOW_STORE(domain, name) \
static ssize_t kyber_##name##_lat_show(struct elevator_queue *e, \
char *page) \
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{ \
struct kyber_queue_data *kqd = e->elevator_data; \
\
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
return sprintf(page, "%llu\n", kqd->latency_targets[domain]); \
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
} \
\
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
static ssize_t kyber_##name##_lat_store(struct elevator_queue *e, \
const char *page, size_t count) \
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
{ \
struct kyber_queue_data *kqd = e->elevator_data; \
unsigned long long nsec; \
int ret; \
\
ret = kstrtoull(page, 10, &nsec); \
if (ret) \
return ret; \
\
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
kqd->latency_targets[domain] = nsec; \
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
\
return count; \
}
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
KYBER_LAT_SHOW_STORE(KYBER_READ, read);
KYBER_LAT_SHOW_STORE(KYBER_WRITE, write);
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
#undef KYBER_LAT_SHOW_STORE
#define KYBER_LAT_ATTR(op) __ATTR(op##_lat_nsec, 0644, kyber_##op##_lat_show, kyber_##op##_lat_store)
static struct elv_fs_entry kyber_sched_attrs[] = {
KYBER_LAT_ATTR(read),
KYBER_LAT_ATTR(write),
__ATTR_NULL
};
#undef KYBER_LAT_ATTR
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
#ifdef CONFIG_BLK_DEBUG_FS
#define KYBER_DEBUGFS_DOMAIN_ATTRS(domain, name) \
static int kyber_##name##_tokens_show(void *data, struct seq_file *m) \
{ \
struct request_queue *q = data; \
struct kyber_queue_data *kqd = q->elevator->elevator_data; \
\
sbitmap_queue_show(&kqd->domain_tokens[domain], m); \
return 0; \
} \
\
static void *kyber_##name##_rqs_start(struct seq_file *m, loff_t *pos) \
__acquires(&khd->lock) \
{ \
struct blk_mq_hw_ctx *hctx = m->private; \
struct kyber_hctx_data *khd = hctx->sched_data; \
\
spin_lock(&khd->lock); \
return seq_list_start(&khd->rqs[domain], *pos); \
} \
\
static void *kyber_##name##_rqs_next(struct seq_file *m, void *v, \
loff_t *pos) \
{ \
struct blk_mq_hw_ctx *hctx = m->private; \
struct kyber_hctx_data *khd = hctx->sched_data; \
\
return seq_list_next(v, &khd->rqs[domain], pos); \
} \
\
static void kyber_##name##_rqs_stop(struct seq_file *m, void *v) \
__releases(&khd->lock) \
{ \
struct blk_mq_hw_ctx *hctx = m->private; \
struct kyber_hctx_data *khd = hctx->sched_data; \
\
spin_unlock(&khd->lock); \
} \
\
static const struct seq_operations kyber_##name##_rqs_seq_ops = { \
.start = kyber_##name##_rqs_start, \
.next = kyber_##name##_rqs_next, \
.stop = kyber_##name##_rqs_stop, \
.show = blk_mq_debugfs_rq_show, \
}; \
\
static int kyber_##name##_waiting_show(void *data, struct seq_file *m) \
{ \
struct blk_mq_hw_ctx *hctx = data; \
struct kyber_hctx_data *khd = hctx->sched_data; \
sched/wait: Rename wait_queue_t => wait_queue_entry_t Rename: wait_queue_t => wait_queue_entry_t 'wait_queue_t' was always a slight misnomer: its name implies that it's a "queue", but in reality it's a queue *entry*. The 'real' queue is the wait queue head, which had to carry the name. Start sorting this out by renaming it to 'wait_queue_entry_t'. This also allows the real structure name 'struct __wait_queue' to lose its double underscore and become 'struct wait_queue_entry', which is the more canonical nomenclature for such data types. Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:13 +07:00
wait_queue_entry_t *wait = &khd->domain_wait[domain]; \
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
\
sched/wait: Disambiguate wq_entry->task_list and wq_head->task_list naming So I've noticed a number of instances where it was not obvious from the code whether ->task_list was for a wait-queue head or a wait-queue entry. Furthermore, there's a number of wait-queue users where the lists are not for 'tasks' but other entities (poll tables, etc.), in which case the 'task_list' name is actively confusing. To clear this all up, name the wait-queue head and entry list structure fields unambiguously: struct wait_queue_head::task_list => ::head struct wait_queue_entry::task_list => ::entry For example, this code: rqw->wait.task_list.next != &wait->task_list ... is was pretty unclear (to me) what it's doing, while now it's written this way: rqw->wait.head.next != &wait->entry ... which makes it pretty clear that we are iterating a list until we see the head. Other examples are: list_for_each_entry_safe(pos, next, &x->task_list, task_list) { list_for_each_entry(wq, &fence->wait.task_list, task_list) { ... where it's unclear (to me) what we are iterating, and during review it's hard to tell whether it's trying to walk a wait-queue entry (which would be a bug), while now it's written as: list_for_each_entry_safe(pos, next, &x->head, entry) { list_for_each_entry(wq, &fence->wait.head, entry) { Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: linux-kernel@vger.kernel.org Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-06-20 17:06:46 +07:00
seq_printf(m, "%d\n", !list_empty_careful(&wait->entry)); \
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
return 0; \
}
KYBER_DEBUGFS_DOMAIN_ATTRS(KYBER_READ, read)
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
KYBER_DEBUGFS_DOMAIN_ATTRS(KYBER_WRITE, write)
KYBER_DEBUGFS_DOMAIN_ATTRS(KYBER_DISCARD, discard)
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
KYBER_DEBUGFS_DOMAIN_ATTRS(KYBER_OTHER, other)
#undef KYBER_DEBUGFS_DOMAIN_ATTRS
static int kyber_async_depth_show(void *data, struct seq_file *m)
{
struct request_queue *q = data;
struct kyber_queue_data *kqd = q->elevator->elevator_data;
seq_printf(m, "%u\n", kqd->async_depth);
return 0;
}
static int kyber_cur_domain_show(void *data, struct seq_file *m)
{
struct blk_mq_hw_ctx *hctx = data;
struct kyber_hctx_data *khd = hctx->sched_data;
kyber: add tracepoints When debugging Kyber, it's really useful to know what latencies we've been having, how the domain depths have been adjusted, and if we've actually been throttling. Add three tracepoints, kyber_latency, kyber_adjust, and kyber_throttled, to record that. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:55 +07:00
seq_printf(m, "%s\n", kyber_domain_names[khd->cur_domain]);
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
return 0;
}
static int kyber_batching_show(void *data, struct seq_file *m)
{
struct blk_mq_hw_ctx *hctx = data;
struct kyber_hctx_data *khd = hctx->sched_data;
seq_printf(m, "%u\n", khd->batching);
return 0;
}
#define KYBER_QUEUE_DOMAIN_ATTRS(name) \
{#name "_tokens", 0400, kyber_##name##_tokens_show}
static const struct blk_mq_debugfs_attr kyber_queue_debugfs_attrs[] = {
KYBER_QUEUE_DOMAIN_ATTRS(read),
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
KYBER_QUEUE_DOMAIN_ATTRS(write),
KYBER_QUEUE_DOMAIN_ATTRS(discard),
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
KYBER_QUEUE_DOMAIN_ATTRS(other),
{"async_depth", 0400, kyber_async_depth_show},
{},
};
#undef KYBER_QUEUE_DOMAIN_ATTRS
#define KYBER_HCTX_DOMAIN_ATTRS(name) \
{#name "_rqs", 0400, .seq_ops = &kyber_##name##_rqs_seq_ops}, \
{#name "_waiting", 0400, kyber_##name##_waiting_show}
static const struct blk_mq_debugfs_attr kyber_hctx_debugfs_attrs[] = {
KYBER_HCTX_DOMAIN_ATTRS(read),
kyber: implement improved heuristics Kyber's current heuristics have a few flaws: - It's based on the mean latency, but p99 latency tends to be more meaningful to anyone who cares about latency. The mean can also be skewed by rare outliers that the scheduler can't do anything about. - The statistics calculations are purely time-based with a short window. This works for steady, high load, but is more sensitive to outliers with bursty workloads. - It only considers the latency once an I/O has been submitted to the device, but the user cares about the time spent in the kernel, as well. These are shortcomings of the generic blk-stat code which doesn't quite fit the ideal use case for Kyber. So, this replaces the statistics with a histogram used to calculate percentiles of total latency and I/O latency, which we then use to adjust depths in a slightly more intelligent manner: - Sync and async writes are now the same domain. - Discards are a separate domain. - Domain queue depths are scaled by the ratio of the p99 total latency to the target latency (e.g., if the p99 latency is double the target latency, we will double the queue depth; if the p99 latency is half of the target latency, we can halve the queue depth). - We use the I/O latency to determine whether we should scale queue depths down: we will only scale down if any domain's I/O latency exceeds the target latency, which is an indicator of congestion in the device. These new heuristics are just as scalable as the heuristics they replace. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-09-28 05:55:54 +07:00
KYBER_HCTX_DOMAIN_ATTRS(write),
KYBER_HCTX_DOMAIN_ATTRS(discard),
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
KYBER_HCTX_DOMAIN_ATTRS(other),
{"cur_domain", 0400, kyber_cur_domain_show},
{"batching", 0400, kyber_batching_show},
{},
};
#undef KYBER_HCTX_DOMAIN_ATTRS
#endif
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
static struct elevator_type kyber_sched = {
.ops.mq = {
.init_sched = kyber_init_sched,
.exit_sched = kyber_exit_sched,
.init_hctx = kyber_init_hctx,
.exit_hctx = kyber_exit_hctx,
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
.limit_depth = kyber_limit_depth,
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
.bio_merge = kyber_bio_merge,
blk-mq-sched: unify request prepare methods This patch makes sure we always allocate requests in the core blk-mq code and use a common prepare_request method to initialize them for both mq I/O schedulers. For Kyber and additional limit_depth method is added that is called before allocating the request. Also because none of the intializations can really fail the new method does not return an error - instead the bfq finish method is hardened to deal with the no-IOC case. Last but not least this removes the abuse of RQF_QUEUE by the blk-mq scheduling code as RQF_ELFPRIV is all that is needed now. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:26 +07:00
.prepare_request = kyber_prepare_request,
block: kyber: make kyber more friendly with merging Currently, kyber is very unfriendly with merging. kyber depends on ctx rq_list to do merging, however, most of time, it will not leave any requests in ctx rq_list. This is because even if tokens of one domain is used up, kyber will try to dispatch requests from other domain and flush the rq_list there. To improve this, we setup kyber_ctx_queue (kcq) which is similar with ctx, but it has rq_lists for different domain and build same mapping between kcq and khd as the ctx & hctx. Then we could merge, insert and dispatch for different domains separately. At the same time, only flush the rq_list of kcq when get domain token successfully. Then if one domain token is used up, the requests could be left in the rq_list of that domain and maybe merged with following io. Following is my test result on machine with 8 cores and NVMe card INTEL SSDPEKKR128G7 fio size=256m ioengine=libaio iodepth=64 direct=1 numjobs=8 seq/random +------+---------------------------------------------------------------+ |patch?| bw(MB/s) | iops | slat(usec) | clat(usec) | merge | +----------------------------------------------------------------------+ | w/o | 606/612 | 151k/153k | 6.89/7.03 | 3349.21/3305.40 | 0/0 | +----------------------------------------------------------------------+ | w/ | 1083/616 | 277k/154k | 4.93/6.95 | 1830.62/3279.95 | 223k/3k | +----------------------------------------------------------------------+ When set numjobs to 16, the bw and iops could reach 1662MB/s and 425k on my platform. Signed-off-by: Jianchao Wang <jianchao.w.wang@oracle.com> Tested-by: Holger Hoffstätte <holger@applied-asynchrony.com> Reviewed-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-05-30 23:47:40 +07:00
.insert_requests = kyber_insert_requests,
blk-mq-sched: unify request finished methods No need to have two different callouts of bfq vs kyber. Signed-off-by: Christoph Hellwig <hch@lst.de> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2017-06-16 23:15:21 +07:00
.finish_request = kyber_finish_request,
block: kyber: fix domain token leak during requeue When requeuing request, the domain token should have been freed before re-inserting the request to io scheduler. Otherwise, the assigned domain token will be leaked, and IO hang can be caused. Cc: Paolo Valente <paolo.valente@linaro.org> Cc: Omar Sandoval <osandov@fb.com> Cc: stable@vger.kernel.org Reviewed-by: Bart Van Assche <bart.vanassche@wdc.com> Signed-off-by: Ming Lei <ming.lei@redhat.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2018-02-23 22:36:57 +07:00
.requeue_request = kyber_finish_request,
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
.completed_request = kyber_completed_request,
.dispatch_request = kyber_dispatch_request,
.has_work = kyber_has_work,
},
.uses_mq = true,
kyber: add debugfs attributes Expose the domain token pools, asynchronous sbitmap depth, domain request lists, and batching state. Signed-off-by: Omar Sandoval <osandov@fb.com> Reviewed-by: Hannes Reinecke <hare@suse.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-05-04 14:31:33 +07:00
#ifdef CONFIG_BLK_DEBUG_FS
.queue_debugfs_attrs = kyber_queue_debugfs_attrs,
.hctx_debugfs_attrs = kyber_hctx_debugfs_attrs,
#endif
blk-mq: introduce Kyber multiqueue I/O scheduler The Kyber I/O scheduler is an I/O scheduler for fast devices designed to scale to multiple queues. Users configure only two knobs, the target read and synchronous write latencies, and the scheduler tunes itself to achieve that latency goal. The implementation is based on "tokens", built on top of the scalable bitmap library. Tokens serve as a mechanism for limiting requests. There are two tiers of tokens: queueing tokens and dispatch tokens. A queueing token is required to allocate a request. In fact, these tokens are actually the blk-mq internal scheduler tags, but the scheduler manages the allocation directly in order to implement its policy. Dispatch tokens are device-wide and split up into two scheduling domains: reads vs. writes. Each hardware queue dispatches batches round-robin between the scheduling domains as long as tokens are available for that domain. These tokens can be used as the mechanism to enable various policies. The policy Kyber uses is inspired by active queue management techniques for network routing, similar to blk-wbt. The scheduler monitors latencies and scales the number of dispatch tokens accordingly. Queueing tokens are used to prevent starvation of synchronous requests by asynchronous requests. Various extensions are possible, including better heuristics and ionice support. The new scheduler isn't set as the default yet. Signed-off-by: Omar Sandoval <osandov@fb.com> Signed-off-by: Jens Axboe <axboe@fb.com>
2017-04-14 15:00:02 +07:00
.elevator_attrs = kyber_sched_attrs,
.elevator_name = "kyber",
.elevator_owner = THIS_MODULE,
};
static int __init kyber_init(void)
{
return elv_register(&kyber_sched);
}
static void __exit kyber_exit(void)
{
elv_unregister(&kyber_sched);
}
module_init(kyber_init);
module_exit(kyber_exit);
MODULE_AUTHOR("Omar Sandoval");
MODULE_LICENSE("GPL");
MODULE_DESCRIPTION("Kyber I/O scheduler");
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