1. 19 4月, 2017 8 次提交
    • P
      block, bfq: improve responsiveness · 44e44a1b
      Paolo Valente 提交于
      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.pdfSigned-off-by: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      44e44a1b
    • P
      block, bfq: add more fairness with writes and slow processes · c074170e
      Paolo Valente 提交于
      This patch deals with two sources of unfairness, which can also cause
      high latencies and throughput loss. The first source is related to
      write requests. Write requests tend to starve read requests, basically
      because, on one side, writes are slower than reads, whereas, on the
      other side, storage devices confuse schedulers by deceptively
      signaling the completion of write requests immediately after receiving
      them. This patch addresses this issue by just throttling writes. In
      particular, after a write request is dispatched for a queue, the
      budget of the queue is decremented by the number of sectors to write,
      multiplied by an (over)charge coefficient. The value of the
      coefficient is the result of our tuning with different devices.
      
      The second source of unfairness has to do with slowness detection:
      when the in-service queue is expired, BFQ also controls whether the
      queue has been "too slow", i.e., has consumed its last-assigned budget
      at such a low rate that it would have been impossible to consume all
      of this budget within the maximum time slice T_max (Subsec. 3.5 in
      [1]). In this case, the queue is always (over)charged the whole
      budget, to reduce its utilization of the device. Both this overcharge
      and the slowness-detection criterion may cause unfairness.
      
      First, always charging a full budget to a slow queue is too coarse. It
      is much more accurate, and this patch lets BFQ do so, to charge an
      amount of service 'equivalent' to the amount of time during which the
      queue has been in service. As explained in more detail in the comments
      on the code, this enables BFQ to provide time fairness among slow
      queues.
      
      Secondly, because of ZBR, a queue may be deemed as slow when its
      associated process is performing I/O on the slowest zones of a
      disk. However, unless the process is truly too slow, not reducing the
      disk utilization of the queue is more profitable in terms of disk
      throughput than the opposite. A similar problem is caused by logical
      block mapping on non-rotational devices. For this reason, this patch
      lets a queue be charged time, and not budget, only if the queue has
      consumed less than 2/3 of its assigned budget. As an additional,
      important benefit, this tolerance allows BFQ to preserve enough
      elasticity to still perform bandwidth, and not time, distribution with
      little unlucky or quasi-sequential processes.
      
      Finally, for the same reasons as above, this patch makes slowness
      detection itself much less harsh: a queue is deemed slow only if it
      has consumed its budget at less than half of the peak rate.
      
      [1] 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: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      c074170e
    • P
      block, bfq: modify the peak-rate estimator · ab0e43e9
      Paolo Valente 提交于
      Unless the maximum budget B_max that BFQ can assign to a queue is set
      explicitly by the user, BFQ automatically updates B_max. In
      particular, BFQ dynamically sets B_max to the number of sectors that
      can be read, at the current estimated peak rate, during the maximum
      time, T_max, allowed before a budget timeout occurs. In formulas, if
      we denote as R_est the estimated peak rate, then B_max = T_max ∗
      R_est. Hence, the higher R_est is with respect to the actual device
      peak rate, the higher the probability that processes incur budget
      timeouts unjustly is. Besides, a too high value of B_max unnecessarily
      increases the deviation from an ideal, smooth service.
      
      Unfortunately, it is not trivial to estimate the peak rate correctly:
      because of the presence of sw and hw queues between the scheduler and
      the device components that finally serve I/O requests, it is hard to
      say exactly when a given dispatched request is served inside the
      device, and for how long. As a consequence, it is hard to know
      precisely at what rate a given set of requests is actually served by
      the device.
      
      On the opposite end, the dispatch time of any request is trivially
      available, and, from this piece of information, the "dispatch rate"
      of requests can be immediately computed. So, the idea in the next
      function is to use what is known, namely request dispatch times
      (plus, when useful, request completion times), to estimate what is
      unknown, namely in-device request service rate.
      
      The main issue is that, because of the above facts, the rate at
      which a certain set of requests is dispatched over a certain time
      interval can vary greatly with respect to the rate at which the
      same requests are then served. But, since the size of any
      intermediate queue is limited, and the service scheme is lossless
      (no request is silently dropped), the following obvious convergence
      property holds: the number of requests dispatched MUST become
      closer and closer to the number of requests completed as the
      observation interval grows. This is the key property used in
      this new version of the peak-rate estimator.
      Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      ab0e43e9
    • P
      block, bfq: improve throughput boosting · 54b60456
      Paolo Valente 提交于
      The feedback-loop algorithm used by BFQ to compute queue (process)
      budgets is basically a set of three update rules, one for each of the
      main reasons why a queue may be expired. If many processes suddenly
      switch from sporadic I/O to greedy and sequential I/O, then these
      rules are quite slow to assign large budgets to these processes, and
      hence to achieve a high throughput. On the opposite side, BFQ assigns
      the maximum possible budget B_max to a just-created queue. This allows
      a high throughput to be achieved immediately if the associated process
      is I/O-bound and performs sequential I/O from the beginning. But it
      also increases the worst-case latency experienced by the first
      requests issued by the process, because the larger the budget of a
      queue waiting for service is, the later the queue will be served by
      B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or
      soft real-time application.
      
      To tackle these throughput and latency problems, on one hand this
      patch changes the initial budget value to B_max/2. On the other hand,
      it re-tunes the three rules, adopting a more aggressive,
      multiplicative increase/linear decrease scheme. This scheme trades
      latency for throughput more than before, and tends to assign large
      budgets quickly to processes that are or become I/O-bound. For two of
      the expiration reasons, the new version of the rules also contains
      some more little improvements, briefly described below.
      
      *No more backlog.* In this case, the budget was larger than the number
      of sectors actually read/written by the process before it stopped
      doing I/O. Hence, to reduce latency for the possible future I/O
      requests of the process, the old rule simply set the next budget to
      the number of sectors actually consumed by the process. However, if
      there are still outstanding requests, then the process may have not
      yet issued its next request just because it is still waiting for the
      completion of some of the still outstanding ones. If this sub-case
      holds true, then the new rule, instead of decreasing the budget,
      doubles it, proactively, in the hope that: 1) a larger budget will fit
      the actual needs of the process, and 2) the process is sequential and
      hence a higher throughput will be achieved by serving the process
      longer after granting it access to the device.
      
      *Budget timeout*. The original rule set the new budget to the maximum
      value B_max, to maximize throughput and let all processes experiencing
      budget timeouts receive the same share of the device time. In our
      experiments we verified that this sudden jump to B_max did not provide
      sensible benefits; rather it increased the latency of processes
      performing sporadic and short I/O. The new rule only doubles the
      budget.
      
      [1] 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: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      54b60456
    • A
      block, bfq: add full hierarchical scheduling and cgroups support · e21b7a0b
      Arianna Avanzini 提交于
      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: NFabio Checconi <fchecconi@gmail.com>
      Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      e21b7a0b
    • P
      block, bfq: introduce the BFQ-v0 I/O scheduler as an extra scheduler · aee69d78
      Paolo Valente 提交于
      We tag as v0 the version of BFQ containing only BFQ's engine plus
      hierarchical support. BFQ's engine is introduced by this commit, while
      hierarchical support is added by next commit. We use the v0 tag to
      distinguish this minimal version of BFQ from the versions containing
      also the features and the improvements added by next commits. BFQ-v0
      coincides with the version of BFQ submitted a few years ago [1], apart
      from the introduction of preemption, described below.
      
      BFQ is a proportional-share I/O scheduler, whose general structure,
      plus a lot of code, are borrowed from CFQ.
      
      - Each process doing I/O on a device is associated with a weight and a
        (bfq_)queue.
      
      - BFQ grants exclusive access to the device, for a while, to one queue
        (process) at a time, and implements this service model by
        associating every queue with a budget, measured in number of
        sectors.
      
        - After a queue is granted access to the device, the budget of the
          queue is decremented, on each request dispatch, by the size of the
          request.
      
        - The in-service queue is expired, i.e., its service is suspended,
          only if one of the following events occurs: 1) the queue finishes
          its budget, 2) the queue empties, 3) a "budget timeout" fires.
      
          - The budget timeout prevents processes doing random I/O from
            holding the device for too long and dramatically reducing
            throughput.
      
          - Actually, as in CFQ, a queue associated with a process issuing
            sync requests may not be expired immediately when it empties. In
            contrast, BFQ may idle the device for a short time interval,
            giving the process the chance to go on being served if it issues
            a new request in time. Device idling typically boosts the
            throughput on rotational devices, if processes do synchronous
            and sequential I/O. In addition, under BFQ, device idling is
            also instrumental in guaranteeing the desired throughput
            fraction to processes issuing sync requests (see [2] for
            details).
      
            - With respect to idling for service guarantees, if several
              processes are competing for the device at the same time, but
              all processes (and groups, after the following commit) have
              the same weight, then BFQ guarantees the expected throughput
              distribution without ever idling the device. Throughput is
              thus as high as possible in this common scenario.
      
        - Queues are scheduled according to a variant of WF2Q+, named
          B-WF2Q+, and implemented using an augmented rb-tree to preserve an
          O(log N) overall complexity.  See [2] for more details. B-WF2Q+ is
          also ready for hierarchical scheduling. However, for a cleaner
          logical breakdown, the code that enables and completes
          hierarchical support is provided in the next commit, which focuses
          exactly on this feature.
      
        - B-WF2Q+ guarantees a tight deviation with respect to an ideal,
          perfectly fair, and smooth service. In particular, B-WF2Q+
          guarantees that each queue receives a fraction of the device
          throughput proportional to its weight, even if the throughput
          fluctuates, and regardless of: the device parameters, the current
          workload and the budgets assigned to the queue.
      
        - The last, budget-independence, property (although probably
          counterintuitive in the first place) is definitely beneficial, for
          the following reasons:
      
          - First, with any proportional-share scheduler, the maximum
            deviation with respect to an ideal service is proportional to
            the maximum budget (slice) assigned to queues. As a consequence,
            BFQ can keep this deviation tight not only because of the
            accurate service of B-WF2Q+, but also because BFQ *does not*
            need to assign a larger budget to a queue to let the queue
            receive a higher fraction of the device throughput.
      
          - Second, BFQ is free to choose, for every process (queue), the
            budget that best fits the needs of the process, or best
            leverages the I/O pattern of the process. In particular, BFQ
            updates queue budgets with a simple feedback-loop algorithm that
            allows a high throughput to be achieved, while still providing
            tight latency guarantees to time-sensitive applications. When
            the in-service queue expires, this algorithm computes the next
            budget of the queue so as to:
      
            - Let large budgets be eventually assigned to the queues
              associated with I/O-bound applications performing sequential
              I/O: in fact, the longer these applications are served once
              got access to the device, the higher the throughput is.
      
            - Let small budgets be eventually assigned to the queues
              associated with time-sensitive applications (which typically
              perform sporadic and short I/O), because, the smaller the
              budget assigned to a queue waiting for service is, the sooner
              B-WF2Q+ will serve that queue (Subsec 3.3 in [2]).
      
      - Weights can be assigned to processes only indirectly, through I/O
        priorities, and according to the relation:
        weight = 10 * (IOPRIO_BE_NR - ioprio).
        The next patch provides, instead, a cgroups interface through which
        weights can be assigned explicitly.
      
      - If several processes are competing for the device at the same time,
        but all processes and groups have the same weight, then BFQ
        guarantees the expected throughput distribution without ever idling
        the device. It uses preemption instead. Throughput is then much
        higher in this common scenario.
      
      - ioprio classes are served in strict priority order, i.e.,
        lower-priority queues are not served as long as there are
        higher-priority queues.  Among queues in the same class, the
        bandwidth is distributed in proportion to the weight of each
        queue. A very thin extra bandwidth is however guaranteed to the Idle
        class, to prevent it from starving.
      
      - If the strict_guarantees parameter is set (default: unset), then BFQ
           - always performs idling when the in-service queue becomes empty;
           - forces the device to serve one I/O request at a time, by
             dispatching a new request only if there is no outstanding
             request.
        In the presence of differentiated weights or I/O-request sizes,
        both the above conditions are needed to guarantee that every
        queue receives its allotted share of the bandwidth (see
        Documentation/block/bfq-iosched.txt for more details). Setting
        strict_guarantees may evidently affect throughput.
      
      [1] https://lkml.org/lkml/2008/4/1/234
          https://lkml.org/lkml/2008/11/11/148
      
      [2] P. Valente and M. Andreolini, "Improving Application
          Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
          the 5th Annual International Systems and Storage Conference
          (SYSTOR '12), June 2012.
          Slightly extended version:
          http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
      							results.pdf
      Signed-off-by: NFabio Checconi <fchecconi@gmail.com>
      Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
      Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      aee69d78
    • J
      nbd: set the max segment size to UINT_MAX · ebb16d0d
      Josef Bacik 提交于
      NBD doesn't care about limiting the segment size, let the user push the
      largest bio's they want.  This allows us to control the request size
      solely through max_sectors_kb.
      Signed-off-by: NJosef Bacik <jbacik@fb.com>
      Reviewed-by: NMing Lei <ming.lei@redhat.com>
      Signed-off-by: NJens Axboe <axboe@fb.com>
      ebb16d0d
    • J
      Merge branch 'stable/for-jens-4.12' of... · 6af38473
      Jens Axboe 提交于
      Merge branch 'stable/for-jens-4.12' of git://git.kernel.org/pub/scm/linux/kernel/git/konrad/xen into for-4.12/block
      
      Konrad writes:
      
      It has one fix - to emit an uevent whenever the size of the guest disk image
      changes.
      6af38473
  2. 18 4月, 2017 1 次提交
  3. 17 4月, 2017 31 次提交