![Paolo Valente](/assets/img/avatar_default.png)
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>
547 lines
23 KiB
Plaintext
547 lines
23 KiB
Plaintext
BFQ (Budget Fair Queueing)
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==========================
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BFQ is a proportional-share I/O scheduler, with some extra
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low-latency capabilities. In addition to cgroups support (blkio or io
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controllers), BFQ's main features are:
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- BFQ guarantees a high system and application responsiveness, and a
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low latency for time-sensitive applications, such as audio or video
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players;
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- BFQ distributes bandwidth, and not just time, among processes or
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groups (switching back to time distribution when needed to keep
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throughput high).
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In its default configuration, BFQ privileges latency over
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throughput. So, when needed for achieving a lower latency, BFQ builds
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schedules that may lead to a lower throughput. If your main or only
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goal, for a given device, is to achieve the maximum-possible
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throughput at all times, then do switch off all low-latency heuristics
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for that device, by setting low_latency to 0. Full details in Section 3.
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On average CPUs, the current version of BFQ can handle devices
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performing at most ~30K IOPS; at most ~50 KIOPS on faster CPUs. As a
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reference, 30-50 KIOPS correspond to very high bandwidths with
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sequential I/O (e.g., 8-12 GB/s if I/O requests are 256 KB large), and
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to 120-200 MB/s with 4KB random I/O. BFQ has not yet been tested on
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multi-queue devices.
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The table of contents follow. Impatients can just jump to Section 3.
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CONTENTS
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1. When may BFQ be useful?
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1-1 Personal systems
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1-2 Server systems
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2. How does BFQ work?
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3. What are BFQ's tunable?
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4. BFQ group scheduling
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4-1 Service guarantees provided
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4-2 Interface
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1. When may BFQ be useful?
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==========================
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BFQ provides the following benefits on personal and server systems.
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1-1 Personal systems
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--------------------
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Low latency for interactive applications
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Regardless of the actual background workload, BFQ guarantees that, for
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interactive tasks, the storage device is virtually as responsive as if
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it was idle. For example, even if one or more of the following
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background workloads are being executed:
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- one or more large files are being read, written or copied,
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- a tree of source files is being compiled,
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- one or more virtual machines are performing I/O,
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- a software update is in progress,
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- indexing daemons are scanning filesystems and updating their
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databases,
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starting an application or loading a file from within an application
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takes about the same time as if the storage device was idle. As a
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comparison, with CFQ, NOOP or DEADLINE, and in the same conditions,
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applications experience high latencies, or even become unresponsive
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until the background workload terminates (also on SSDs).
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Low latency for soft real-time applications
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Also soft real-time applications, such as audio and video
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players/streamers, enjoy a low latency and a low drop rate, regardless
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of the background I/O workload. As a consequence, these applications
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do not suffer from almost any glitch due to the background workload.
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Higher speed for code-development tasks
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If some additional workload happens to be executed in parallel, then
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BFQ executes the I/O-related components of typical code-development
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tasks (compilation, checkout, merge, ...) much more quickly than CFQ,
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NOOP or DEADLINE.
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High throughput
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On hard disks, BFQ achieves up to 30% higher throughput than CFQ, and
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up to 150% higher throughput than DEADLINE and NOOP, with all the
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sequential workloads considered in our tests. With random workloads,
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and with all the workloads on flash-based devices, BFQ achieves,
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instead, about the same throughput as the other schedulers.
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Strong fairness, bandwidth and delay guarantees
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BFQ distributes the device throughput, and not just the device time,
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among I/O-bound applications in proportion their weights, with any
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workload and regardless of the device parameters. From these bandwidth
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guarantees, it is possible to compute tight per-I/O-request delay
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guarantees by a simple formula. If not configured for strict service
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guarantees, BFQ switches to time-based resource sharing (only) for
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applications that would otherwise cause a throughput loss.
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1-2 Server systems
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------------------
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Most benefits for server systems follow from the same service
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properties as above. In particular, regardless of whether additional,
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possibly heavy workloads are being served, BFQ guarantees:
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. audio and video-streaming with zero or very low jitter and drop
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rate;
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. fast retrieval of WEB pages and embedded objects;
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. real-time recording of data in live-dumping applications (e.g.,
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packet logging);
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. responsiveness in local and remote access to a server.
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2. How does BFQ work?
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=====================
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BFQ is a proportional-share I/O scheduler, whose general structure,
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plus a lot of code, are borrowed from CFQ.
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- Each process doing I/O on a device is associated with a weight and a
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(bfq_)queue.
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- BFQ grants exclusive access to the device, for a while, to one queue
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(process) at a time, and implements this service model by
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associating every queue with a budget, measured in number of
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sectors.
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- After a queue is granted access to the device, the budget of the
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queue is decremented, on each request dispatch, by the size of the
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request.
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- The in-service queue is expired, i.e., its service is suspended,
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only if one of the following events occurs: 1) the queue finishes
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its budget, 2) the queue empties, 3) a "budget timeout" fires.
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- The budget timeout prevents processes doing random I/O from
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holding the device for too long and dramatically reducing
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throughput.
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- Actually, as in CFQ, a queue associated with a process issuing
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sync requests may not be expired immediately when it empties. In
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contrast, BFQ may idle the device for a short time interval,
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giving the process the chance to go on being served if it issues
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a new request in time. Device idling typically boosts the
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throughput on rotational devices, if processes do synchronous
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and sequential I/O. In addition, under BFQ, device idling is
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also instrumental in guaranteeing the desired throughput
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fraction to processes issuing sync requests (see the description
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of the slice_idle tunable in this document, or [1, 2], for more
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details).
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- With respect to idling for service guarantees, if several
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processes are competing for the device at the same time, but
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all processes (and groups, after the following commit) have
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the same weight, then BFQ guarantees the expected throughput
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distribution without ever idling the device. Throughput is
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thus as high as possible in this common scenario.
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- If low-latency mode is enabled (default configuration), BFQ
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executes some special heuristics to detect interactive and soft
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real-time applications (e.g., video or audio players/streamers),
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and to reduce their latency. The most important action taken to
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achieve this goal is to give to the queues associated with these
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applications more than their fair share of the device
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throughput. For brevity, we call just "weight-raising" the whole
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sets of actions taken by BFQ to privilege these queues. In
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particular, BFQ provides a milder form of weight-raising for
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interactive applications, and a stronger form for soft real-time
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applications.
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- BFQ automatically deactivates idling for queues born in a burst of
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queue creations. In fact, these queues are usually associated with
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the processes of applications and services that benefit mostly
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from a high throughput. Examples are systemd during boot, or git
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grep.
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- As CFQ, BFQ merges queues performing interleaved I/O, i.e.,
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performing random I/O that becomes mostly sequential if
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merged. Differently from CFQ, BFQ achieves this goal with a more
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reactive mechanism, called Early Queue Merge (EQM). EQM is so
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responsive in detecting interleaved I/O (cooperating processes),
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that it enables BFQ to achieve a high throughput, by queue
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merging, even for queues for which CFQ needs a different
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mechanism, preemption, to get a high throughput. As such EQM is a
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unified mechanism to achieve a high throughput with interleaved
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I/O.
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- Queues are scheduled according to a variant of WF2Q+, named
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B-WF2Q+, and implemented using an augmented rb-tree to preserve an
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O(log N) overall complexity. See [2] for more details. B-WF2Q+ is
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also ready for hierarchical scheduling. However, for a cleaner
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logical breakdown, the code that enables and completes
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hierarchical support is provided in the next commit, which focuses
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exactly on this feature.
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- B-WF2Q+ guarantees a tight deviation with respect to an ideal,
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perfectly fair, and smooth service. In particular, B-WF2Q+
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guarantees that each queue receives a fraction of the device
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throughput proportional to its weight, even if the throughput
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fluctuates, and regardless of: the device parameters, the current
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workload and the budgets assigned to the queue.
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- The last, budget-independence, property (although probably
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counterintuitive in the first place) is definitely beneficial, for
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the following reasons:
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- First, with any proportional-share scheduler, the maximum
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deviation with respect to an ideal service is proportional to
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the maximum budget (slice) assigned to queues. As a consequence,
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BFQ can keep this deviation tight not only because of the
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accurate service of B-WF2Q+, but also because BFQ *does not*
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need to assign a larger budget to a queue to let the queue
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receive a higher fraction of the device throughput.
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- Second, BFQ is free to choose, for every process (queue), the
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budget that best fits the needs of the process, or best
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leverages the I/O pattern of the process. In particular, BFQ
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updates queue budgets with a simple feedback-loop algorithm that
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allows a high throughput to be achieved, while still providing
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tight latency guarantees to time-sensitive applications. When
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the in-service queue expires, this algorithm computes the next
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budget of the queue so as to:
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- Let large budgets be eventually assigned to the queues
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associated with I/O-bound applications performing sequential
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I/O: in fact, the longer these applications are served once
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got access to the device, the higher the throughput is.
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- Let small budgets be eventually assigned to the queues
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associated with time-sensitive applications (which typically
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perform sporadic and short I/O), because, the smaller the
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budget assigned to a queue waiting for service is, the sooner
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B-WF2Q+ will serve that queue (Subsec 3.3 in [2]).
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- If several processes are competing for the device at the same time,
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but all processes and groups have the same weight, then BFQ
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guarantees the expected throughput distribution without ever idling
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the device. It uses preemption instead. Throughput is then much
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higher in this common scenario.
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- ioprio classes are served in strict priority order, i.e.,
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lower-priority queues are not served as long as there are
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higher-priority queues. Among queues in the same class, the
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bandwidth is distributed in proportion to the weight of each
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queue. A very thin extra bandwidth is however guaranteed to
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the Idle class, to prevent it from starving.
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3. What are BFQ's tunable?
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==========================
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The tunables back_seek-max, back_seek_penalty, fifo_expire_async and
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fifo_expire_sync below are the same as in CFQ. Their description is
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just copied from that for CFQ. Some considerations in the description
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of slice_idle are copied from CFQ too.
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per-process ioprio and weight
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-----------------------------
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Unless the cgroups interface is used (see "4. BFQ group scheduling"),
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weights can be assigned to processes only indirectly, through I/O
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priorities, and according to the relation:
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weight = (IOPRIO_BE_NR - ioprio) * 10.
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Beware that, if low-latency is set, then BFQ automatically raises the
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weight of the queues associated with interactive and soft real-time
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applications. Unset this tunable if you need/want to control weights.
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slice_idle
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----------
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This parameter specifies how long BFQ should idle for next I/O
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request, when certain sync BFQ queues become empty. By default
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slice_idle is a non-zero value. Idling has a double purpose: boosting
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throughput and making sure that the desired throughput distribution is
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respected (see the description of how BFQ works, and, if needed, the
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papers referred there).
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As for throughput, idling can be very helpful on highly seeky media
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like single spindle SATA/SAS disks where we can cut down on overall
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number of seeks and see improved throughput.
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Setting slice_idle to 0 will remove all the idling on queues and one
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should see an overall improved throughput on faster storage devices
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like multiple SATA/SAS disks in hardware RAID configuration.
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So depending on storage and workload, it might be useful to set
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slice_idle=0. In general for SATA/SAS disks and software RAID of
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SATA/SAS disks keeping slice_idle enabled should be useful. For any
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configurations where there are multiple spindles behind single LUN
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(Host based hardware RAID controller or for storage arrays), setting
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slice_idle=0 might end up in better throughput and acceptable
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latencies.
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Idling is however necessary to have service guarantees enforced in
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case of differentiated weights or differentiated I/O-request lengths.
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To see why, suppose that a given BFQ queue A must get several I/O
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requests served for each request served for another queue B. Idling
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ensures that, if A makes a new I/O request slightly after becoming
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empty, then no request of B is dispatched in the middle, and thus A
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does not lose the possibility to get more than one request dispatched
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before the next request of B is dispatched. Note that idling
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guarantees the desired differentiated treatment of queues only in
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terms of I/O-request dispatches. To guarantee that the actual service
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order then corresponds to the dispatch order, the strict_guarantees
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tunable must be set too.
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There is an important flipside for idling: apart from the above cases
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where it is beneficial also for throughput, idling can severely impact
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throughput. One important case is random workload. Because of this
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issue, BFQ tends to avoid idling as much as possible, when it is not
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beneficial also for throughput. As a consequence of this behavior, and
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of further issues described for the strict_guarantees tunable,
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short-term service guarantees may be occasionally violated. And, in
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some cases, these guarantees may be more important than guaranteeing
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maximum throughput. For example, in video playing/streaming, a very
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low drop rate may be more important than maximum throughput. In these
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cases, consider setting the strict_guarantees parameter.
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strict_guarantees
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-----------------
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If this parameter is set (default: unset), then BFQ
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- always performs idling when the in-service queue becomes empty;
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- forces the device to serve one I/O request at a time, by dispatching a
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new request only if there is no outstanding request.
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In the presence of differentiated weights or I/O-request sizes, both
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the above conditions are needed to guarantee that every BFQ queue
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receives its allotted share of the bandwidth. The first condition is
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needed for the reasons explained in the description of the slice_idle
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tunable. The second condition is needed because all modern storage
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devices reorder internally-queued requests, which may trivially break
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the service guarantees enforced by the I/O scheduler.
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Setting strict_guarantees may evidently affect throughput.
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back_seek_max
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-------------
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This specifies, given in Kbytes, the maximum "distance" for backward seeking.
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The distance is the amount of space from the current head location to the
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sectors that are backward in terms of distance.
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This parameter allows the scheduler to anticipate requests in the "backward"
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direction and consider them as being the "next" if they are within this
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distance from the current head location.
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back_seek_penalty
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-----------------
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This parameter is used to compute the cost of backward seeking. If the
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backward distance of request is just 1/back_seek_penalty from a "front"
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request, then the seeking cost of two requests is considered equivalent.
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So scheduler will not bias toward one or the other request (otherwise scheduler
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will bias toward front request). Default value of back_seek_penalty is 2.
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fifo_expire_async
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-----------------
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This parameter is used to set the timeout of asynchronous requests. Default
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value of this is 248ms.
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fifo_expire_sync
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----------------
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This parameter is used to set the timeout of synchronous requests. Default
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value of this is 124ms. In case to favor synchronous requests over asynchronous
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one, this value should be decreased relative to fifo_expire_async.
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low_latency
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-----------
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This parameter is used to enable/disable BFQ's low latency mode. By
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default, low latency mode is enabled. If enabled, interactive and soft
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real-time applications are privileged and experience a lower latency,
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as explained in more detail in the description of how BFQ works.
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DISABLE this mode if you need full control on bandwidth
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distribution. In fact, if it is enabled, then BFQ automatically
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increases the bandwidth share of privileged applications, as the main
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means to guarantee a lower latency to them.
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In addition, as already highlighted at the beginning of this document,
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DISABLE this mode if your only goal is to achieve a high throughput.
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In fact, privileging the I/O of some application over the rest may
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entail a lower throughput. To achieve the highest-possible throughput
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on a non-rotational device, setting slice_idle to 0 may be needed too
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(at the cost of giving up any strong guarantee on fairness and low
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latency).
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timeout_sync
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------------
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Maximum amount of device time that can be given to a task (queue) once
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it has been selected for service. On devices with costly seeks,
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increasing this time usually increases maximum throughput. On the
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opposite end, increasing this time coarsens the granularity of the
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short-term bandwidth and latency guarantees, especially if the
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following parameter is set to zero.
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max_budget
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----------
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Maximum amount of service, measured in sectors, that can be provided
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to a BFQ queue once it is set in service (of course within the limits
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of the above timeout). According to what said in the description of
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the algorithm, larger values increase the throughput in proportion to
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the percentage of sequential I/O requests issued. The price of larger
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values is that they coarsen the granularity of short-term bandwidth
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and latency guarantees.
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The default value is 0, which enables auto-tuning: BFQ sets max_budget
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to the maximum number of sectors that can be served during
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timeout_sync, according to the estimated peak rate.
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weights
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-------
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Read-only parameter, used to show the weights of the currently active
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BFQ queues.
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wr_ tunables
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------------
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BFQ exports a few parameters to control/tune the behavior of
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low-latency heuristics.
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wr_coeff
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Factor by which the weight of a weight-raised queue is multiplied. If
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the queue is deemed soft real-time, then the weight is further
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multiplied by an additional, constant factor.
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wr_max_time
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Maximum duration of a weight-raising period for an interactive task
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(ms). If set to zero (default value), then this value is computed
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automatically, as a function of the peak rate of the device. In any
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case, when the value of this parameter is read, it always reports the
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current duration, regardless of whether it has been set manually or
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computed automatically.
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wr_max_softrt_rate
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Maximum service rate below which a queue is deemed to be associated
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with a soft real-time application, and is then weight-raised
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accordingly (sectors/sec).
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wr_min_idle_time
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Minimum idle period after which interactive weight-raising may be
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reactivated for a queue (in ms).
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wr_rt_max_time
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Maximum weight-raising duration for soft real-time queues (in ms). The
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start time from which this duration is considered is automatically
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moved forward if the queue is detected to be still soft real-time
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before the current soft real-time weight-raising period finishes.
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wr_min_inter_arr_async
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Minimum period between I/O request arrivals after which weight-raising
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may be reactivated for an already busy async queue (in ms).
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4. Group scheduling with BFQ
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============================
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BFQ supports both cgroups-v1 and cgroups-v2 io controllers, namely
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blkio and io. In particular, BFQ supports weight-based proportional
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share. To activate cgroups support, set BFQ_GROUP_IOSCHED.
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4-1 Service guarantees provided
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-------------------------------
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With BFQ, proportional share means true proportional share of the
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device bandwidth, according to group weights. For example, a group
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with weight 200 gets twice the bandwidth, and not just twice the time,
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of a group with weight 100.
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BFQ supports hierarchies (group trees) of any depth. Bandwidth is
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distributed among groups and processes in the expected way: for each
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group, the children of the group share the whole bandwidth of the
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group in proportion to their weights. In particular, this implies
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that, for each leaf group, every process of the group receives the
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same share of the whole group bandwidth, unless the ioprio of the
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process is modified.
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The resource-sharing guarantee for a group may partially or totally
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switch from bandwidth to time, if providing bandwidth guarantees to
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the group lowers the throughput too much. This switch occurs on a
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per-process basis: if a process of a leaf group causes throughput loss
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if served in such a way to receive its share of the bandwidth, then
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BFQ switches back to just time-based proportional share for that
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process.
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4-2 Interface
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-------------
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To get proportional sharing of bandwidth with BFQ for a given device,
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BFQ must of course be the active scheduler for that device.
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Within each group directory, the names of the files associated with
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BFQ-specific cgroup parameters and stats begin with the "bfq."
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prefix. So, with cgroups-v1 or cgroups-v2, the full prefix for
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BFQ-specific files is "blkio.bfq." or "io.bfq." For example, the group
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parameter to set the weight of a group with BFQ is blkio.bfq.weight
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or io.bfq.weight.
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Parameters to set
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-----------------
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For each group, there is only the following parameter to set.
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weight (namely blkio.bfq.weight or io.bfq-weight): the weight of the
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group inside its parent. Available values: 1..10000 (default 100). The
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linear mapping between ioprio and weights, described at the beginning
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of the tunable section, is still valid, but all weights higher than
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IOPRIO_BE_NR*10 are mapped to ioprio 0.
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Recall that, if low-latency is set, then BFQ automatically raises the
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weight of the queues associated with interactive and soft real-time
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applications. Unset this tunable if you need/want to control weights.
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[1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
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Scheduler", Proceedings of the First Workshop on Mobile System
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Technologies (MST-2015), May 2015.
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http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdf
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[2] P. Valente and M. Andreolini, "Improving Application
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Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
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the 5th Annual International Systems and Storage Conference
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(SYSTOR '12), June 2012.
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Slightly extended version:
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http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
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results.pdf
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