Package jsr166y.forkjoin

A fine-grained parallel computation framework.

See: Description

Package jsr166y.forkjoin Description

A fine-grained parallel computation framework. ForkJoinTasks and their related support classes provide a very efficient basis for obtaining platform-independent parallel speed-ups of computation-intensive operations. They are not a full substitute for the kinds of arbitrary processing supported by Executors or Threads. However, when applicable, they typically provide significantly greater performance on multiprocessor platforms.

Candidates for fork/join processing mainly include those that can be expressed using parallel divide-and-conquer techniques: To solve a problem, break it in two (or more) parts, and then solve those parts in parallel, continuing on in this way until the problem is too small to be broken up, so is solved directly. The underlying work-stealing framework makes subtasks available to other threads (normally one per CPU), that help complete the tasks. In general, the most efficient ForkJoinTasks are those that directly implement this algorithmic design pattern.

While direct implementation of parallel divide-and-conquer algorithms is often straightforward, it can also be tedious and code-intensive. For this reason, a number of solution "templates" are available for common kinds of operations on lists and arrays: applying some operation to all elements, combining elements according to some function, and so on. In this preliminary release, these are presented via some interfaces describing the associated code bodies in TaskTypes, along with an evolving set of implementations for lists and arrays of objects and scalars.