FreeBSD/Linux Kernel Cross Reference
sys/Documentation/workqueue.txt

     
     Concurrency Managed Workqueue (cmwq)
     
     September, 2010         Tejun Heo <tj@kernel.org>
                             Florian Mickler <florian@mickler.org>
     
     CONTENTS
     
     1. Introduction
    2. Why cmwq?
    3. The Design
    4. Application Programming Interface (API)
    5. Example Execution Scenarios
    6. Guidelines
    7. Debugging
    
    
    1. 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.
    
    
    2. 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.  A MT wq could provide only one execution context per CPU
    while a 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.
    
    
    3. 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 thread-pools.
    
    The cmwq design differentiates between the user-facing workqueues that
    subsystems and drivers queue work items on and the backend mechanism
    which manages thread-pools and processes the queued work items.
    
    The backend is called gcwq.  There is one gcwq for each possible CPU
    and one gcwq to serve work items queued on unbound workqueues.  Each
    gcwq has two thread-pools - one for normal work items and the other
    for high priority ones.
    
    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, reentrancy, 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 gcwq and
   thread-pool is determined according to the queue parameters and
   workqueue attributes and appended on the shared worklist of the
   thread-pool.  For example, unless specifically overridden, a work item
   of a bound workqueue will be queued on the worklist of either normal
   or highpri thread-pool of the gcwq 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 thread-pool bound to an actual CPU implements concurrency
   management by hooking into the scheduler.  The thread-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 thread-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 an unbound wq, the above concurrency management doesn't apply and
   the thread-pools for the pseudo unbound CPU try to start executing all
   work items as soon as possible.  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 thread-pool deadlocks waiting
   for execution contexts to free up.
   
   
   4. 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_NON_REENTRANT
   
           By default, a wq guarantees non-reentrance only on the same
           CPU.  A work item may not be executed concurrently on the same
           CPU by multiple workers but is allowed to be executed
           concurrently on multiple CPUs.  This flag makes sure
           non-reentrance is enforced across all CPUs.  Work items queued
           to a non-reentrant wq are guaranteed to be executed by at most
           one worker system-wide at any given time.
   
     WQ_UNBOUND
   
           Work items queued to an unbound wq are served by a special
           gcwq which hosts 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 gcwq
           tries 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
           thread-pool of the target gcwq.  Highpri thread-pools are
           served by worker threads with elevated nice level.
   
           Note that normal and highpri thread-pools don't interact with
           each other.  Each maintain 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
           thread-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 is used to achieve this
   behavior.  Work items on such wq are always queued to the unbound gcwq
   and only one work item can be active at any given time thus achieving
   the same ordering property as ST wq.
   
   
   5. 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
   
   
   6. 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.
   
   
   7. 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 beeing 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.

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