workqueue: add documentation

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

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-pool 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.

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 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 is

determined according to the queue parameters and workqueue attributes

and appended on the shared worklist of the gcwq.  For example, unless

specifically overridden, a work item of a bound workqueue will be

queued on the worklist of exactly that 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 gcwq bound to an actual CPU implements concurrency management by

hooking into the scheduler.  The gcwq 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 gcwq 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 gcwq for the pseudo unbound CPU tries 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_FREEZEABLE

	A freezeable 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_RESCUER

	All wq which might be used in the memory reclaim paths _MUST_

	have this flag set.  This reserves one worker exclusively for

	the execution of this wq under memory pressure.

  WQ_HIGHPRI

	Work items of a highpri wq are queued at the head of the

	worklist of the target gcwq and start execution regardless of

	the current concurrency level.  In other words, highpri work

	items will always start execution as soon as execution

	resource is available.

	Ordering among highpri work items is preserved - a highpri

	work item queued after another highpri work item will start

	execution after the earlier highpri work item starts.

	Although highpri work items are not held back by other

	runnable work items, they still contribute to the concurrency

	level.  Highpri work items in runnable state will prevent

	non-highpri work items from starting execution.

	This flag is meaningless for unbound wq.

  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 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.

  WQ_HIGHPRI | WQ_CPU_INTENSIVE

	This combination makes the wq avoid interaction with

	concurrency management completely and behave as a simple

	per-CPU execution context provider.  Work items queued on a

	highpri CPU-intensive wq start execution as soon as resources

	are available and don't affect execution of other work items.

@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_HIGHPRI set,

 TIME IN MSECS	EVENT

 0		w1 and w2 start and burn CPU

 5		w1 sleeps

 10		w2 sleeps

 10		w0 starts and burns CPU

 15		w0 sleeps

 15		w1 wakes up and finishes

 20		w2 wakes up and finishes

 25		w0 wakes up and burns CPU

 30		w0 finishes

If q1 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_RESCUER if a wq may process work items which

  are used during memory reclaim.  Each wq with WQ_RESCUER set has one

  rescuer thread 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_RESCUER.

* 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_RESCUER),

  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.

#define work_clear_pending(work) \

	clear_bit(WORK_STRUCT_PENDING_BIT, work_data_bits(work))

/*

 * Workqueue flags and constants.  For details, please refer to

 * Documentation/workqueue.txt.

 */

enum {

	WQ_NON_REENTRANT	= 1 << 0, /* guarantee non-reentrance */

	WQ_UNBOUND		= 1 << 1, /* not bound to any cpu */

/*

 * linux/kernel/workqueue.c

 * kernel/workqueue.c - generic async execution with shared worker pool

 *

 * Generic mechanism for defining kernel helper threads for running

 * arbitrary tasks in process context.

 *

 * Started by Ingo Molnar, Copyright (C) 2002

 * Copyright (C) 2002		Ingo Molnar

 *

 *   Derived from the taskqueue/keventd code by:

 *

 *     David Woodhouse <dwmw2@infradead.org>

 *     Andrew Morton

 *     Kai Petzke <wpp@marie.physik.tu-berlin.de>

 *     Theodore Ts'o <tytso@mit.edu>

 *

 * Made to use alloc_percpu by Christoph Lameter.

 *

 * Copyright (C) 2010		SUSE Linux Products GmbH

 * Copyright (C) 2010		Tejun Heo <tj@kernel.org>

 *

 * This is the generic async execution mechanism.  Work items as are

 * executed in process context.  The worker pool is shared and

 * automatically managed.  There is one worker pool for each CPU and

 * one extra for works which are better served by workers which are

 * not bound to any specific CPU.

 *

 * Please read Documentation/workqueue.txt for details.

 */

#include <linux/module.h>