[PATCH V2 00/22] Replace the CFQ I/O Scheduler with BFQ

From: Paolo Valente
Date: Mon Aug 08 2016 - 07:20:48 EST

[This patchset, based against v4.8-rc1, replaces my last-submitted
series, wrongly tagged as V8]

Hi,
this new version of the patchset contains the improvements and bug
fixes recommended by Tejun [7], plus new features of BFQ-v8r2. Details
about old and new features in patch descriptions. For your
convenience, here is the usual description of the overall patchset.

This patchset replaces CFQ with the last version of BFQ (which is a
proportional-share I/O scheduler). To make a smooth transition, this
patchset first brings CFQ back to its state at the time when BFQ was
forked from CFQ. Basically, this reduces CFQ to its engine, by
removing every heuristic and improvement that has nothing to do with
any heuristic or improvement in BFQ, and every heuristic and
improvement whose goal is achieved in a different way in BFQ. Then,
the second part of the patchset starts by replacing CFQ's engine with
BFQ's engine, and goes on by adding current BFQ improvements and extra
heuristics. Here is the thread in which we agreed on both this first
step, and the second and last step: [1]. Moreover, here is a direct
link to the email describing both steps: [2].

Some patch generates WARNINGS with checkpatch.pl, but these WARNINGS
seem to be either unavoidable for the involved pieces of code (which
the patch just extends), or false positives.

Turning back to BFQ, its first version was submitted a few years ago
[3]. It is denoted as v0 in this patchset, to distinguish it from the
version I am submitting now, v8r2. In particular, the first two
patches concerned with BFQ introduce BFQ-v0, whereas the remaining
patches turn progressively BFQ-v0 into BFQ-v8. Here are some nice
features of BFQ-v8r2.

Low latency for interactive applications

According to our results, and regardless of the actual background
workload, for interactive tasks the storage device is virtually as
responsive as if it was idle. For example, even if one or more of the
following background workloads are being executed:
- one or more large files are being read or written,
- a tree of source files is being compiled,
- one or more virtual machines are performing I/O,
- a software update is in progress,
- indexing daemons are scanning filesystems and updating their
databases,
starting an application or loading a file from within an application
takes about the same time as if the storage device was idle. As a
comparison, with CFQ, NOOP or DEADLINE, and in the same conditions,
applications experience high latencies, or even become unresponsive
until the background workload terminates (also on SSDs).

Low latency for soft real-time applications

Also soft real-time applications, such as audio and video
players/streamers, enjoy a low latency and a low drop rate, regardless
of the background I/O workload. As a consequence, these applications
do not suffer from almost any glitch due to the background workload.

High throughput

On hard disks, BFQ achieves up to 30% higher throughput than CFQ, and
up to 150% higher throughput than DEADLINE and NOOP, with half of the
parallel workloads considered in our tests. With the rest of the
workloads, and with all the workloads on flash-based devices, BFQ
achieves instead about the same throughput as the other schedulers.

Strong fairness guarantees (already provided by BFQ-v0)

As for long-term guarantees, BFQ distributes the device throughput
(and not just the device time) as desired among I/O-bound
applications, with any workload and regardless of the device
parameters.


BFQ achieves the above service properties thanks to the combination of
its accurate scheduling engine (patches 9-10), and a set of simple
heuristics and improvements (patches 11-22). Details on how BFQ and
its components work are provided in the descriptions of the
patches. In addition, an organic description of the main BFQ algorithm
and of most of its features can be found in this paper [4].

What BFQ can do in practice is shown, e.g., in this 8-minute demo with
an SSD: [5]. I made this demo with an older version of BFQ (v7r6) and
under Linux 3.17.0, but, for the tests considered in the demo,
performance has remained about the same with more recent BFQ and
kernel versions. More details about this point can be found here [6],
together with graphs showing the performance of BFQ, as compared with
CFQ, DEADLINE and NOOP, and on: a fast and a slow hard disk, a RAID1,
an SSD, a microSDHC Card and an eMMC. As an example, our results on
the SSD are reported also in a table at the end of this email.

Finally, as for testing in everyday use, BFQ is the default I/O
scheduler in, e.g., Manjaro, Sabayon, OpenMandriva and Arch Linux ARM,
plus several kernel forks for PCs and smartphones. In addition, BFQ is
optionally available in, e.g., Arch, PCLinuxOS and Gentoo, and we
record several downloads a day from people using other
distributions. The feedback received so far basically confirms the
expected latency drop and throughput boost.

Paolo

Results on a Plextor PX-256M5S SSD

The first two rows of the next table report the aggregate throughput
achieved by BFQ, CFQ, DEADLINE and NOOP, while ten parallel processes
read, either sequentially or randomly, a separate portion of the
memory blocks each. These processes read directly from the device, and
no process performs writes, to avoid writing large files repeatedly
and wearing out the device during the many tests done. As can be seen,
all schedulers achieve about the same throughput with sequential
readers, whereas, with random readers, the throughput slightly grows
as the complexity, and hence the execution time, of the schedulers
decreases. In fact, with random readers, the number of IOPS is
extremely higher, and all CPUs spend all the time either executing
instructions or waiting for I/O (the total idle percentage is
0). Therefore, the processing time of I/O requests influences the
maximum throughput achievable.

The remaining rows report the cold-cache start-up time experienced by
various applications while one of the above two workloads is being
executed in parallel. In particular, "Start-up time 10 seq/rand"
stands for "Start-up time of the application at hand while 10
sequential/random readers are running". A timeout fires, and the test
is aborted, if the application does not start within 60 seconds; so,
in the table, '>60' means that the application did not start before
the timeout fired.

With sequential readers, the performance gap between BFQ and the other
schedulers is remarkable. Background workloads are intentionally very
heavy, to show the performance of the schedulers in somewhat extreme
conditions. Differences are however still significant also with
lighter workloads, as shown, e.g., here [6] for slower devices.

-----------------------------------------------------------------------------
| SCHEDULER | Test |
-----------------------------------------------------------------------------
| BFQ | CFQ | DEADLINE | NOOP | |
-----------------------------------------------------------------------------
| | | | | Aggregate Throughput |
| | | | | [MB/s] |
| 399 | 400 | 400 | 400 | 10 raw seq. readers |
| 191 | 193 | 202 | 203 | 10 raw random readers |
-----------------------------------------------------------------------------
| | | | | Start-up time 10 seq |
| | | | | [sec] |
| 0.21 | >60 | 1.91 | 1.88 | xterm |
| 0.93 | >60 | 10.2 | 10.8 | oowriter |
| 0.89 | >60 | 29.7 | 30.0 | konsole |
-----------------------------------------------------------------------------
| | | | | Start-up time 10 rand |
| | | | | [sec] |
| 0.20 | 0.30 | 0.21 | 0.21 | xterm |
| 0.81 | 3.28 | 0.80 | 0.81 | oowriter |
| 0.88 | 2.90 | 1.02 | 1.00 | konsole |
-----------------------------------------------------------------------------


[1] https://lkml.org/lkml/2014/5/27/314

[2] https://lists.linux-foundation.org/pipermail/containers/2014-June/034704.html

[3] https://lkml.org/lkml/2008/4/1/234

[4] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
Scheduler", Proceedings of the First Workshop on Mobile System
Technologies (MST-2015), May 2015.
http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf

[5] https://youtu.be/1cjZeaCXIyM

[6] http://algogroup.unimore.it/people/paolo/disk_sched/results.php

[7] https://lkml.org/lkml/2016/2/1/818

Arianna Avanzini (11):
block, cfq: remove queue merging for close cooperators
block, cfq: remove close-based preemption
block, cfq: remove deep seek queues logic
block, cfq: remove SSD-related logic
block, cfq: get rid of hierarchical support
block, cfq: get rid of queue preemption
block, cfq: get rid of workload type
block, bfq: add full hierarchical scheduling and cgroups support
block, bfq: add Early Queue Merge (EQM)
block, bfq: reduce idling only in symmetric scenarios
block, bfq: handle bursts of queue activations

Paolo Valente (11):
block, cfq: get rid of latency tunables
block, cfq: replace CFQ with the BFQ-v0 I/O scheduler
block, bfq: improve throughput boosting
block, bfq: modify the peak-rate estimator
block, bfq: add more fairness with writes and slow processes
block, bfq: improve responsiveness
block, bfq: reduce I/O latency for soft real-time applications
block, bfq: preserve a low latency also with NCQ-capable drives
block, bfq: reduce latency during request-pool saturation
block, bfq: boost the throughput on NCQ-capable flash-based devices
block, bfq: boost the throughput with random I/O on NCQ-capable HDDs

block/Kconfig.iosched | 19 +-
block/cfq-iosched.c | 9859 ++++++++++++++++++++++++++++++++-----------------
2 files changed, 6440 insertions(+), 3438 deletions(-)

--
1.9.1