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 ====================================
 Concurrency Managed Workqueue (cmwq)
 ====================================
 
 :Date: September, 2010
 :Author: Tejun Heo <tj@kernel.org>
 :Author: Florian Mickler <florian@mickler.org>
 
 
 Introduction
 ============
 
 There are many cases where an asynchronous process execution context
 is needed and the workqueue (wq) API is the most commonly used
 mechanism for such cases.
 
 When such an asynchronous execution context is needed, a work item
 describing which function to execute is put on a queue.  An
 independent thread serves as the asynchronous execution context.  The
 queue is called workqueue and the thread is called worker.
 
 While there are work items on the workqueue the worker executes the
 functions associated with the work items one after the other.  When
 there is no work item left on the workqueue the worker becomes idle.
 When a new work item gets queued, the worker begins executing again.
 
 
 Why cmwq?
 =========
 
 In the original wq implementation, a multi threaded (MT) wq had one
 worker thread per CPU and a single threaded (ST) wq had one worker
 thread system-wide.  A single MT wq needed to keep around the same
 number of workers as the number of CPUs.  The kernel grew a lot of MT
 wq users over the years and with the number of CPU cores continuously
 rising, some systems saturated the default 32k PID space just booting
 up.
 
 Although MT wq wasted a lot of resource, the level of concurrency
 provided was unsatisfactory.  The limitation was common to both ST and
 MT wq albeit less severe on MT.  Each wq maintained its own separate
 worker pool.  An MT wq could provide only one execution context per CPU
 while an ST wq one for the whole system.  Work items had to compete for
 those very limited execution contexts leading to various problems
 including proneness to deadlocks around the single execution context.
 
 The tension between the provided level of concurrency and resource
 usage also forced its users to make unnecessary tradeoffs like libata
 choosing to use ST wq for polling PIOs and accepting an unnecessary
 limitation that no two polling PIOs can progress at the same time.  As
 MT wq don't provide much better concurrency, users which require
 higher level of concurrency, like async or fscache, had to implement
 their own thread pool.
 
 Concurrency Managed Workqueue (cmwq) is a reimplementation of wq with
 focus on the following goals.
 
 * Maintain compatibility with the original workqueue API.
 
 * Use per-CPU unified worker pools shared by all wq to provide
   flexible level of concurrency on demand without wasting a lot of
   resource.
 
 * Automatically regulate worker pool and level of concurrency so that
   the API users don't need to worry about such details.
 
 
 The Design
 ==========
 
 In order to ease the asynchronous execution of functions a new
 abstraction, the work item, is introduced.
 
 A work item is a simple struct that holds a pointer to the function
 that is to be executed asynchronously.  Whenever a driver or subsystem
 wants a function to be executed asynchronously it has to set up a work
 item pointing to that function and queue that work item on a
 workqueue.
 
 Special purpose threads, called worker threads, execute the functions
 off of the queue, one after the other.  If no work is queued, the
 worker threads become idle.  These worker threads are managed in so
 called worker-pools.
 
 The cmwq design differentiates between the user-facing workqueues that
 subsystems and drivers queue work items on and the backend mechanism
 which manages worker-pools and processes the queued work items.
 
 There are two worker-pools, one for normal work items and the other
 for high priority ones, for each possible CPU and some extra
 worker-pools to serve work items queued on unbound workqueues - the
 number of these backing pools is dynamic.
 
 Subsystems and drivers can create and queue work items through special
 workqueue API functions as they see fit. They can influence some
 aspects of the way the work items are executed by setting flags on the
 workqueue they are putting the work item on. These flags include
 things like CPU locality, concurrency limits, priority and more.  To
 get a detailed overview refer to the API description of
 ``alloc_workqueue()`` below.
 
 When a work item is queued to a workqueue, the target worker-pool is
 determined according to the queue parameters and workqueue attributes
 and appended on the shared worklist of the worker-pool.  For example,
 unless specifically overridden, a work item of a bound workqueue will
 be queued on the worklist of either normal or highpri worker-pool that
 is associated to the CPU the issuer is running on.
 
 For any worker pool implementation, managing the concurrency level
 (how many execution contexts are active) is an important issue.  cmwq
 tries to keep the concurrency at a minimal but sufficient level.
 Minimal to save resources and sufficient in that the system is used at
 its full capacity.
 
 Each worker-pool bound to an actual CPU implements concurrency
 management by hooking into the scheduler.  The worker-pool is notified
 whenever an active worker wakes up or sleeps and keeps track of the
 number of the currently runnable workers.  Generally, work items are
 not expected to hog a CPU and consume many cycles.  That means
 maintaining just enough concurrency to prevent work processing from
 stalling should be optimal.  As long as there are one or more runnable
 workers on the CPU, the worker-pool doesn't start execution of a new
 work, but, when the last running worker goes to sleep, it immediately
 schedules a new worker so that the CPU doesn't sit idle while there
 are pending work items.  This allows using a minimal number of workers
 without losing execution bandwidth.
 
 Keeping idle workers around doesn't cost other than the memory space
 for kthreads, so cmwq holds onto idle ones for a while before killing
 them.
 
 For unbound workqueues, the number of backing pools is dynamic.
 Unbound workqueue can be assigned custom attributes using
 ``apply_workqueue_attrs()`` and workqueue will automatically create
 backing worker pools matching the attributes.  The responsibility of
 regulating concurrency level is on the users.  There is also a flag to
 mark a bound wq to ignore the concurrency management.  Please refer to
 the API section for details.
 
 Forward progress guarantee relies on that workers can be created when
 more execution contexts are necessary, which in turn is guaranteed
 through the use of rescue workers.  All work items which might be used
 on code paths that handle memory reclaim are required to be queued on
 wq's that have a rescue-worker reserved for execution under memory
 pressure.  Else it is possible that the worker-pool deadlocks waiting
 for execution contexts to free up.
 
 
 Application Programming Interface (API)
 =======================================
 
 ``alloc_workqueue()`` allocates a wq.  The original
 ``create_*workqueue()`` functions are deprecated and scheduled for
 removal.  ``alloc_workqueue()`` takes three arguments - ``@name``,
 ``@flags`` and ``@max_active``.  ``@name`` is the name of the wq and
 also used as the name of the rescuer thread if there is one.
 
 A wq no longer manages execution resources but serves as a domain for
 forward progress guarantee, flush and work item attributes. ``@flags``
 and ``@max_active`` control how work items are assigned execution
 resources, scheduled and executed.
 
 
 ``flags``
 ---------
 
 ``WQ_UNBOUND``
   Work items queued to an unbound wq are served by the special
   worker-pools which host workers which are not bound to any
   specific CPU.  This makes the wq behave as a simple execution
   context provider without concurrency management.  The unbound
   worker-pools try to start execution of work items as soon as
   possible.  Unbound wq sacrifices locality but is useful for
   the following cases.
 
   * Wide fluctuation in the concurrency level requirement is
     expected and using bound wq may end up creating large number
     of mostly unused workers across different CPUs as the issuer
     hops through different CPUs.
 
   * Long running CPU intensive workloads which can be better
     managed by the system scheduler.
 
 ``WQ_FREEZABLE``
   A freezable wq participates in the freeze phase of the system
   suspend operations.  Work items on the wq are drained and no
   new work item starts execution until thawed.
 
 ``WQ_MEM_RECLAIM``
   All wq which might be used in the memory reclaim paths **MUST**
   have this flag set.  The wq is guaranteed to have at least one
   execution context regardless of memory pressure.
 
 ``WQ_HIGHPRI``
   Work items of a highpri wq are queued to the highpri
   worker-pool of the target cpu.  Highpri worker-pools are
   served by worker threads with elevated nice level.
 
   Note that normal and highpri worker-pools don't interact with
   each other.  Each maintains its separate pool of workers and
   implements concurrency management among its workers.
 
 ``WQ_CPU_INTENSIVE``
   Work items of a CPU intensive wq do not contribute to the
   concurrency level.  In other words, runnable CPU intensive
   work items will not prevent other work items in the same
   worker-pool from starting execution.  This is useful for bound
   work items which are expected to hog CPU cycles so that their
   execution is regulated by the system scheduler.
 
   Although CPU intensive work items don't contribute to the
   concurrency level, start of their executions is still
   regulated by the concurrency management and runnable
   non-CPU-intensive work items can delay execution of CPU
   intensive work items.
 
   This flag is meaningless for unbound wq.
 
 
 ``max_active``
 --------------
 
 ``@max_active`` determines the maximum number of execution contexts
 per CPU which can be assigned to the work items of a wq.  For example,
 with ``@max_active`` of 16, at most 16 work items of the wq can be
 executing at the same time per CPU.
 
 Currently, for a bound wq, the maximum limit for ``@max_active`` is
 512 and the default value used when 0 is specified is 256.  For an
 unbound wq, the limit is higher of 512 and 4 *
 ``num_possible_cpus()``.  These values are chosen sufficiently high
 such that they are not the limiting factor while providing protection
 in runaway cases.
 
 The number of active work items of a wq is usually regulated by the
 users of the wq, more specifically, by how many work items the users
 may queue at the same time.  Unless there is a specific need for
 throttling the number of active work items, specifying '0' is
 recommended.
 
 Some users depend on the strict execution ordering of ST wq.  The
 combination of ``@max_active`` of 1 and ``WQ_UNBOUND`` used to
 achieve this behavior.  Work items on such wq were always queued to the
 unbound worker-pools and only one work item could be active at any given
 time thus achieving the same ordering property as ST wq.
 
 In the current implementation the above configuration only guarantees
 ST behavior within a given NUMA node. Instead ``alloc_ordered_queue()`` should
 be used to achieve system-wide ST behavior.
 
 
 Example Execution Scenarios
 ===========================
 
 The following example execution scenarios try to illustrate how cmwq
 behave under different configurations.
 
  Work items w0, w1, w2 are queued to a bound wq q0 on the same CPU.
  w0 burns CPU for 5ms then sleeps for 10ms then burns CPU for 5ms
  again before finishing.  w1 and w2 burn CPU for 5ms then sleep for
  10ms.
 
 Ignoring all other tasks, works and processing overhead, and assuming
 simple FIFO scheduling, the following is one highly simplified version
 of possible sequences of events with the original wq. ::
 
  TIME IN MSECS  EVENT
  0              w0 starts and burns CPU
  5              w0 sleeps
  15             w0 wakes up and burns CPU
  20             w0 finishes
  20             w1 starts and burns CPU
  25             w1 sleeps
  35             w1 wakes up and finishes
  35             w2 starts and burns CPU
  40             w2 sleeps
  50             w2 wakes up and finishes
 
 And with cmwq with ``@max_active`` >= 3, ::
 
  TIME IN MSECS  EVENT
  0              w0 starts and burns CPU
  5              w0 sleeps
  5              w1 starts and burns CPU
  10             w1 sleeps
  10             w2 starts and burns CPU
  15             w2 sleeps
  15             w0 wakes up and burns CPU
  20             w0 finishes
  20             w1 wakes up and finishes
  25             w2 wakes up and finishes
 
 If ``@max_active`` == 2, ::
 
  TIME IN MSECS  EVENT
  0              w0 starts and burns CPU
  5              w0 sleeps
  5              w1 starts and burns CPU
  10             w1 sleeps
  15             w0 wakes up and burns CPU
  20             w0 finishes
  20             w1 wakes up and finishes
  20             w2 starts and burns CPU
  25             w2 sleeps
  35             w2 wakes up and finishes
 
 Now, let's assume w1 and w2 are queued to a different wq q1 which has
 ``WQ_CPU_INTENSIVE`` set, ::
 
  TIME IN MSECS  EVENT
  0              w0 starts and burns CPU
  5              w0 sleeps
  5              w1 and w2 start and burn CPU
  10             w1 sleeps
  15             w2 sleeps
  15             w0 wakes up and burns CPU
  20             w0 finishes
  20             w1 wakes up and finishes
  25             w2 wakes up and finishes
 
 
 Guidelines
 ==========
 
 * Do not forget to use ``WQ_MEM_RECLAIM`` if a wq may process work
   items which are used during memory reclaim.  Each wq with
   ``WQ_MEM_RECLAIM`` set has an execution context reserved for it.  If
   there is dependency among multiple work items used during memory
   reclaim, they should be queued to separate wq each with
   ``WQ_MEM_RECLAIM``.
 
 * Unless strict ordering is required, there is no need to use ST wq.
 
 * Unless there is a specific need, using 0 for @max_active is
   recommended.  In most use cases, concurrency level usually stays
   well under the default limit.
 
 * A wq serves as a domain for forward progress guarantee
   (``WQ_MEM_RECLAIM``, flush and work item attributes.  Work items
   which are not involved in memory reclaim and don't need to be
   flushed as a part of a group of work items, and don't require any
   special attribute, can use one of the system wq.  There is no
   difference in execution characteristics between using a dedicated wq
   and a system wq.
 
 * Unless work items are expected to consume a huge amount of CPU
   cycles, using a bound wq is usually beneficial due to the increased
   level of locality in wq operations and work item execution.
 
 
 Debugging
 =========
 
 Because the work functions are executed by generic worker threads
 there are a few tricks needed to shed some light on misbehaving
 workqueue users.
 
 Worker threads show up in the process list as: ::
 
   root      5671  0.0  0.0      0     0 ?        S    12:07   0:00 [kworker/0:1]
   root      5672  0.0  0.0      0     0 ?        S    12:07   0:00 [kworker/1:2]
   root      5673  0.0  0.0      0     0 ?        S    12:12   0:00 [kworker/0:0]
   root      5674  0.0  0.0      0     0 ?        S    12:13   0:00 [kworker/1:0]
 
 If kworkers are going crazy (using too much cpu), there are two types
 of possible problems:
 
         1. Something being scheduled in rapid succession
         2. A single work item that consumes lots of cpu cycles
 
 The first one can be tracked using tracing: ::
 
         $ echo workqueue:workqueue_queue_work > /sys/kernel/debug/tracing/set_event
         $ cat /sys/kernel/debug/tracing/trace_pipe > out.txt
         (wait a few secs)
         ^C
 
 If something is busy looping on work queueing, it would be dominating
 the output and the offender can be determined with the work item
 function.
 
 For the second type of problems it should be possible to just check
 the stack trace of the offending worker thread. ::
 
         $ cat /proc/THE_OFFENDING_KWORKER/stack
 
 The work item's function should be trivially visible in the stack
 trace.
 
 Non-reentrance Conditions
 =========================
 
 Workqueue guarantees that a work item cannot be re-entrant if the following
 conditions hold after a work item gets queued:
 
         1. The work function hasn't been changed.
         2. No one queues the work item to another workqueue.
         3. The work item hasn't been reinitiated.
 
 In other words, if the above conditions hold, the work item is guaranteed to be
 executed by at most one worker system-wide at any given time.
 
 Note that requeuing the work item (to the same queue) in the self function
 doesn't break these conditions, so it's safe to do. Otherwise, caution is
 required when breaking the conditions inside a work function.
 
 
 Kernel Inline Documentations Reference
 ======================================
 
 .. kernel-doc:: include/linux/workqueue.h
 
 .. kernel-doc:: kernel/workqueue.c

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