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`std.parallelism.TaskPool/taskPool` - multiple declarations

Function taskPool

Returns a lazily initialized global instantiation of TaskPool. This function can safely be called concurrently from multiple non-worker threads. The worker threads in this pool are daemon threads, meaning that it is not necessary to call TaskPool.stop or TaskPool.finish before terminating the main thread.


						
				TaskPool taskPool() @property @trusted;

Class TaskPool

This class encapsulates a task queue and a set of worker threads. Its purpose is to efficiently map a large number of Tasks onto a smaller number of threads. A task queue is a FIFO queue of Task objects that have been submitted to the TaskPool and are awaiting execution. A worker thread is a thread that executes the Task at the front of the queue when one is available and sleeps when the queue is empty.


						
				class TaskPool
				;

This class should usually be used via the global instantiation available via the taskPool property. Occasionally it is useful to explicitly instantiate a TaskPool:

1. When you want TaskPool instances with multiple priorities, for example a low priority pool and a high priority pool.

2. When the threads in the global task pool are waiting on a synchronization primitive (for example a mutex), and you want to parallelize the code that needs to run before these threads can be resumed.

Constructors

Name	Description
`this`	Default constructor that initializes a `TaskPool` with `totalCPUs` - 1 worker threads. The minus 1 is included because the main thread will also be available to do work.
`this`	Allows for custom number of worker threads.

Properties

Name	Type	Description
`isDaemon`[get, set]	`bool`	These properties control whether the worker threads are daemon threads. A daemon thread is automatically terminated when all non-daemon threads have terminated. A non-daemon thread will prevent a program from terminating as long as it has not terminated.
`priority`[get, set]	`int`	These functions allow getting and setting the OS scheduling priority of the worker threads in this `TaskPool`. They forward to `core.thread.Thread.priority`, so a given priority value here means the same thing as an identical priority value in `core.thread`.
`size`[get]	`ulong`	Returns the number of worker threads in the pool.
`workerIndex`[get]	`ulong`	Gets the index of the current thread relative to this `TaskPool`. Any thread not in this pool will receive an index of 0. The worker threads in this pool receive unique indices of 1 through `this.size`.

Methods

Name	Description
`asyncBuf`	Given a `source` range that is expensive to iterate over, returns an input range that asynchronously buffers the contents of `source` into a buffer of `bufSize` elements in a worker thread, while making previously buffered elements from a second buffer, also of size `bufSize`, available via the range interface of the returned object. The returned range has a length iff `hasLength!S`. `asyncBuf` is useful, for example, when performing expensive operations on the elements of ranges that represent data on a disk or network.
`asyncBuf`	Given a callable object `next` that writes to a user-provided buffer and a second callable object `empty` that determines whether more data is available to write via `next`, returns an input range that asynchronously calls `next` with a set of size `nBuffers` of buffers and makes the results available in the order they were obtained via the input range interface of the returned object. Similarly to the input range overload of `asyncBuf`, the first half of the buffers are made available via the range interface while the second half are filled and vice-versa.
`finish`	Signals worker threads to terminate when the queue becomes empty.
`parallel`	Implements a parallel foreach loop over a range. This works by implicitly creating and submitting one `Task` to the `TaskPool` for each worker thread. A work unit is a set of consecutive elements of `range` to be processed by a worker thread between communication with any other thread. The number of elements processed per work unit is controlled by the `workUnitSize` parameter. Smaller work units provide better load balancing, but larger work units avoid the overhead of communicating with other threads frequently to fetch the next work unit. Large work units also avoid false sharing in cases where the range is being modified. The less time a single iteration of the loop takes, the larger `workUnitSize` should be. For very expensive loop bodies, `workUnitSize` should be 1. An overload that chooses a default work unit size is also available.
`put`	Put a `Task` object on the back of the task queue. The `Task` object may be passed by pointer or reference.
`stop`	Signals to all worker threads to terminate as soon as they are finished with their current `Task`, or immediately if they are not executing a `Task`. `Task`s that were in queue will not be executed unless a call to `Task.workForce`, `Task.yieldForce` or `Task.spinForce` causes them to be executed.
`workerLocalStorage`	Creates an instance of worker-local storage, initialized with a given value. The value is `lazy` so that you can, for example, easily create one instance of a class for each worker. For usage example, see the `WorkerLocalStorage` struct.
`factory`	Create instance of class specified by the fully qualified name classname. The class must either have no constructors or have a default constructor.
`opCmp`	Compare with another Object obj.
`opEquals`	Test whether `this` is equal to `o`. The default implementation only compares by identity (using the `is` operator). Generally, overrides for `opEquals` should attempt to compare objects by their contents.
`toHash`	Compute hash function for Object.
`toString`	Convert Object to a human readable string.

Inner structs

Name Description

WorkerLocalStorage Struct for creating worker-local storage. Worker-local storage is thread-local storage that exists only for worker threads in a given TaskPool plus a single thread outside the pool. It is allocated on the garbage collected heap in a way that avoids false sharing, and doesn't necessarily have global scope within any thread. It can be accessed from any worker thread in the TaskPool that created it, and one thread outside this TaskPool. All threads outside the pool that created a given instance of worker-local storage share a single slot.

WorkerLocalStorageRange Range primitives for worker-local storage. The purpose of this is to access results produced by each worker thread from a single thread once you are no longer using the worker-local storage from multiple threads. Do not use this struct in the parallel portion of your algorithm.

Name	Description
`WorkerLocalStorage`	Struct for creating worker-local storage. Worker-local storage is thread-local storage that exists only for worker threads in a given `TaskPool` plus a single thread outside the pool. It is allocated on the garbage collected heap in a way that avoids false sharing, and doesn't necessarily have global scope within any thread. It can be accessed from any worker thread in the `TaskPool` that created it, and one thread outside this `TaskPool`. All threads outside the pool that created a given instance of worker-local storage share a single slot.
`WorkerLocalStorageRange`	Range primitives for worker-local storage. The purpose of this is to access results produced by each worker thread from a single thread once you are no longer using the worker-local storage from multiple threads. Do not use this struct in the parallel portion of your algorithm.

Templates

Name	Description
`amap`
`fold`
`map`
`reduce`

Authors

License

Boost License 1.0