Of the tunables available for the bfq I/O scheduler, the only one
missing from the documentation in 'Documentation/block/bfq-iosched.txt'
is slice_idle_us. Add this tunable to the documentation and a short
explanation of its purpose.
Acked-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: John Pittman <jpittman@redhat.com>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
BFQ currently creates, and updates, its own instance of the whole
set of blkio statistics that cfq creates. Yet, from the comments
of Tejun Heo in [1], it turned out that most of these statistics
are meant/useful only for debugging. This commit makes BFQ create
the latter, debugging statistics only if the option
CONFIG_DEBUG_BLK_CGROUP is set.
By doing so, this commit also enables BFQ to enjoy a high perfomance
boost. The reason is that, if CONFIG_DEBUG_BLK_CGROUP is not set, then
BFQ has to update far fewer statistics, and, in particular, not the
heaviest to update. To give an idea of the benefits, if
CONFIG_DEBUG_BLK_CGROUP is not set, then, on an Intel i7-4850HQ, and
with 8 threads doing random I/O in parallel on null_blk (configured
with 0 latency), the throughput of BFQ grows from 310 to 400 KIOPS
(+30%). We have measured similar or even much higher boosts with other
CPUs: e.g., +45% with an ARM CortexTM-A53 Octa-core. Our results have
been obtained and can be reproduced very easily with the script in [1].
[1] https://www.spinics.net/lists/linux-block/msg18943.html
Suggested-by: Tejun Heo <tj@kernel.org>
Suggested-by: Ulf Hansson <ulf.hansson@linaro.org>
Tested-by: Lee Tibbert <lee.tibbert@gmail.com>
Tested-by: Oleksandr Natalenko <oleksandr@natalenko.name>
Signed-off-by: Luca Miccio <lucmiccio@gmail.com>
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
bfq invokes various blkg_*stats_* functions to update the statistics
contained in the special files blkio.bfq.* in the blkio controller
groups, i.e., the I/O accounting related to the proportional-share
policy provided by bfq. The execution of these functions takes a
considerable percentage, about 40%, of the total per-request execution
time of bfq (i.e., of the sum of the execution time of all the bfq
functions that have to be executed to process an I/O request from its
creation to its destruction). This reduces the request-processing
rate sustainable by bfq noticeably, even on a multicore CPU. In fact,
the bfq functions that invoke blkg_*stats_* functions cannot be
executed in parallel with the rest of the code of bfq, because both
are executed under the same same per-device scheduler lock.
To reduce this slowdown, this commit moves, wherever possible, the
invocation of these functions (more precisely, of the bfq functions
that invoke blkg_*stats_* functions) outside the critical sections
protected by the scheduler lock.
With this change, and with all blkio.bfq.* statistics enabled, the
throughput grows, e.g., from 250 to 310 KIOPS (+25%) on an Intel
i7-4850HQ, in case of 8 threads doing random I/O in parallel on
null_blk, with the latter configured with 0 latency. We obtained the
same or higher throughput boosts, up to +30%, with other processors
(some figures are reported in the documentation). For our tests, we
used the script [1], with which our results can be easily reproduced.
NOTE. This commit still protects the invocation of blkg_*stats_*
functions with the request_queue lock, because the group these
functions are invoked on may otherwise disappear before or while these
functions are executed. Fortunately, tests without even this lock
show, by difference, that the serialization caused by this lock has a
little impact (at most ~5% of throughput reduction).
[1] https://github.com/Algodev-github/IOSpeed
Tested-by: Lee Tibbert <lee.tibbert@gmail.com>
Tested-by: Oleksandr Natalenko <oleksandr@natalenko.name>
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Luca Miccio <lucmiccio@gmail.com>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
We have investigated more deeply the performance of BFQ, in terms of
number of IOPS that can be processed by the CPU when BFQ is used as
I/O scheduler. In more detail, using the script [1], we have measured
the number of IOPS reached on top of a null block device configured
with zero latency, as a function of the workload (sequential read,
sequential write, random read, random write) and of the system (we
considered desktops, laptops and embedded systems).
Basing on the resulting figures, with this commit we update the
current, conservative IOPS range reported in BFQ documentation. In
particular, the documentation now reports, for each of three different
systems, the lowest number of IOPS obtained for that system with the
above test (namely, the value obtained with the workload leading to
the lowest IOPS).
[1] https://github.com/Algodev-github/IOSpeed
Reviewed-by: Lee Tibbert <lee.tibbert@gmail.com>
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Luca Miccio <lucmiccio@gmail.com>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
Many users have reported the lack of an HOWTO for properly configuring
bfq as a function of the goal one wants to achieve (max
responsiveness, max throughput, ...). In fact, all needed details are
already provided in the documentation file bfq-iosched.txt. Yet the
document lacks guidance on which parameter descriptions to look
at. This commit adds some simple direction.
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Reviewed-by: Jeremy Hickman <jeremywh7@gmail.com>
Reviewed-by: Laurentiu Nicola <lnicola@dend.ro>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
In addition to containing some typos and stale sentences, the file
bfq-iosched.txt still mentioned a set of sysfs parameters that have
been removed from this version of bfq. This commit fixes all these
issues.
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Reviewed-by: Jeremy Hickman <jeremywh7@gmail.com>
Reviewed-by: Laurentiu Nicola <lnicola@dend.ro>
Signed-off-by: Jens Axboe <axboe@kernel.dk>
The introduction of the BFQ and Kyber I/O schedulers has triggered a
new wave of I/O benchmarks. Unfortunately, comments and discussions on
these benchmarks confirm that there is still little awareness that it
is very hard to achieve, at the same time, a low latency and a high
throughput. In particular, virtually all benchmarks measure
throughput, or throughput-related figures of merit, but, for BFQ, they
use the scheduler in its default configuration. This configuration is
geared, instead, toward a low latency. This is evidently a sign that
BFQ documentation is still too unclear on this important aspect. This
commit addresses this issue by stressing how BFQ configuration must be
(easily) changed if the only goal is maximum throughput.
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Jens Axboe <axboe@fb.com>
This patch introduces a simple heuristic to load applications quickly,
and to perform the I/O requested by interactive applications just as
quickly. To this purpose, both a newly-created queue and a queue
associated with an interactive application (we explain in a moment how
BFQ decides whether the associated application is interactive),
receive the following two special treatments:
1) The weight of the queue is raised.
2) The queue unconditionally enjoys device idling when it empties; in
fact, if the requests of a queue are sync, then performing device
idling for the queue is a necessary condition to guarantee that the
queue receives a fraction of the throughput proportional to its weight
(see [1] for details).
For brevity, we call just weight-raising the combination of these
two preferential treatments. For a newly-created queue,
weight-raising starts immediately and lasts for a time interval that:
1) depends on the device speed and type (rotational or
non-rotational), and 2) is equal to the time needed to load (start up)
a large-size application on that device, with cold caches and with no
additional workload.
Finally, as for guaranteeing a fast execution to interactive,
I/O-related tasks (such as opening a file), consider that any
interactive application blocks and waits for user input both after
starting up and after executing some task. After a while, the user may
trigger new operations, after which the application stops again, and
so on. Accordingly, the low-latency heuristic weight-raises again a
queue in case it becomes backlogged after being idle for a
sufficiently long (configurable) time. The weight-raising then lasts
for the same time as for a just-created queue.
According to our experiments, the combination of this low-latency
heuristic and of the improvements described in the previous patch
allows BFQ to guarantee a high application responsiveness.
[1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
Scheduler", Proceedings of the First Workshop on Mobile System
Technologies (MST-2015), May 2015.
http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: Jens Axboe <axboe@fb.com>
Add complete support for full hierarchical scheduling, with a cgroups
interface. Full hierarchical scheduling is implemented through the
'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues
associated with processes, and groups are represented in general by
entities. Given the bfq_queues associated with the processes belonging
to a given group, the entities representing these queues are sons of
the entity representing the group. At higher levels, if a group, say
G, contains other groups, then the entity representing G is the parent
entity of the entities representing the groups in G.
Hierarchical scheduling is performed as follows: if the timestamps of
a leaf entity (i.e., of a bfq_queue) change, and such a change lets
the entity become the next-to-serve entity for its parent entity, then
the timestamps of the parent entity are recomputed as a function of
the budget of its new next-to-serve leaf entity. If the parent entity
belongs, in its turn, to a group, and its new timestamps let it become
the next-to-serve for its parent entity, then the timestamps of the
latter parent entity are recomputed as well, and so on. When a new
bfq_queue must be set in service, the reverse path is followed: the
next-to-serve highest-level entity is chosen, then its next-to-serve
child entity, and so on, until the next-to-serve leaf entity is
reached, and the bfq_queue that this entity represents is set in
service.
Writeback is accounted for on a per-group basis, i.e., for each group,
the async I/O requests of the processes of the group are enqueued in a
distinct bfq_queue, and the entity associated with this queue is a
child of the entity associated with the group.
Weights can be assigned explicitly to groups and processes through the
cgroups interface, differently from what happens, for single
processes, if the cgroups interface is not used (as explained in the
description of the previous patch). In particular, since each node has
a full scheduler, each group can be assigned its own weight.
Signed-off-by: Fabio Checconi <fchecconi@gmail.com>
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: Jens Axboe <axboe@fb.com>
We tag as v0 the version of BFQ containing only BFQ's engine plus
hierarchical support. BFQ's engine is introduced by this commit, while
hierarchical support is added by next commit. We use the v0 tag to
distinguish this minimal version of BFQ from the versions containing
also the features and the improvements added by next commits. BFQ-v0
coincides with the version of BFQ submitted a few years ago [1], apart
from the introduction of preemption, described below.
BFQ is a proportional-share I/O scheduler, whose general structure,
plus a lot of code, are borrowed from CFQ.
- Each process doing I/O on a device is associated with a weight and a
(bfq_)queue.
- BFQ grants exclusive access to the device, for a while, to one queue
(process) at a time, and implements this service model by
associating every queue with a budget, measured in number of
sectors.
- After a queue is granted access to the device, the budget of the
queue is decremented, on each request dispatch, by the size of the
request.
- The in-service queue is expired, i.e., its service is suspended,
only if one of the following events occurs: 1) the queue finishes
its budget, 2) the queue empties, 3) a "budget timeout" fires.
- The budget timeout prevents processes doing random I/O from
holding the device for too long and dramatically reducing
throughput.
- Actually, as in CFQ, a queue associated with a process issuing
sync requests may not be expired immediately when it empties. In
contrast, BFQ may idle the device for a short time interval,
giving the process the chance to go on being served if it issues
a new request in time. Device idling typically boosts the
throughput on rotational devices, if processes do synchronous
and sequential I/O. In addition, under BFQ, device idling is
also instrumental in guaranteeing the desired throughput
fraction to processes issuing sync requests (see [2] for
details).
- With respect to idling for service guarantees, if several
processes are competing for the device at the same time, but
all processes (and groups, after the following commit) have
the same weight, then BFQ guarantees the expected throughput
distribution without ever idling the device. Throughput is
thus as high as possible in this common scenario.
- Queues are scheduled according to a variant of WF2Q+, named
B-WF2Q+, and implemented using an augmented rb-tree to preserve an
O(log N) overall complexity. See [2] for more details. B-WF2Q+ is
also ready for hierarchical scheduling. However, for a cleaner
logical breakdown, the code that enables and completes
hierarchical support is provided in the next commit, which focuses
exactly on this feature.
- B-WF2Q+ guarantees a tight deviation with respect to an ideal,
perfectly fair, and smooth service. In particular, B-WF2Q+
guarantees that each queue receives a fraction of the device
throughput proportional to its weight, even if the throughput
fluctuates, and regardless of: the device parameters, the current
workload and the budgets assigned to the queue.
- The last, budget-independence, property (although probably
counterintuitive in the first place) is definitely beneficial, for
the following reasons:
- First, with any proportional-share scheduler, the maximum
deviation with respect to an ideal service is proportional to
the maximum budget (slice) assigned to queues. As a consequence,
BFQ can keep this deviation tight not only because of the
accurate service of B-WF2Q+, but also because BFQ *does not*
need to assign a larger budget to a queue to let the queue
receive a higher fraction of the device throughput.
- Second, BFQ is free to choose, for every process (queue), the
budget that best fits the needs of the process, or best
leverages the I/O pattern of the process. In particular, BFQ
updates queue budgets with a simple feedback-loop algorithm that
allows a high throughput to be achieved, while still providing
tight latency guarantees to time-sensitive applications. When
the in-service queue expires, this algorithm computes the next
budget of the queue so as to:
- Let large budgets be eventually assigned to the queues
associated with I/O-bound applications performing sequential
I/O: in fact, the longer these applications are served once
got access to the device, the higher the throughput is.
- Let small budgets be eventually assigned to the queues
associated with time-sensitive applications (which typically
perform sporadic and short I/O), because, the smaller the
budget assigned to a queue waiting for service is, the sooner
B-WF2Q+ will serve that queue (Subsec 3.3 in [2]).
- Weights can be assigned to processes only indirectly, through I/O
priorities, and according to the relation:
weight = 10 * (IOPRIO_BE_NR - ioprio).
The next patch provides, instead, a cgroups interface through which
weights can be assigned explicitly.
- If several processes are competing for the device at the same time,
but all processes and groups have the same weight, then BFQ
guarantees the expected throughput distribution without ever idling
the device. It uses preemption instead. Throughput is then much
higher in this common scenario.
- ioprio classes are served in strict priority order, i.e.,
lower-priority queues are not served as long as there are
higher-priority queues. Among queues in the same class, the
bandwidth is distributed in proportion to the weight of each
queue. A very thin extra bandwidth is however guaranteed to the Idle
class, to prevent it from starving.
- If the strict_guarantees parameter is set (default: unset), then BFQ
- always performs idling when the in-service queue becomes empty;
- forces the device to serve one I/O request at a time, by
dispatching a new request only if there is no outstanding
request.
In the presence of differentiated weights or I/O-request sizes,
both the above conditions are needed to guarantee that every
queue receives its allotted share of the bandwidth (see
Documentation/block/bfq-iosched.txt for more details). Setting
strict_guarantees may evidently affect throughput.
[1] https://lkml.org/lkml/2008/4/1/234https://lkml.org/lkml/2008/11/11/148
[2] P. Valente and M. Andreolini, "Improving Application
Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
the 5th Annual International Systems and Storage Conference
(SYSTOR '12), June 2012.
Slightly extended version:
http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
results.pdf
Signed-off-by: Fabio Checconi <fchecconi@gmail.com>
Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: Jens Axboe <axboe@fb.com>
John Pittman