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/*
* Written by Doug Lea with assistance from members of JCP JSR-166
* Expert Group and released to the public domain, as explained at
* http://creativecommons.org/publicdomain/zero/1.0/
*/
/**
* Preview versions of classes targeted for Java 7. Includes 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.
*
* <p>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 <em>work-stealing</em> 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.
*/
package scala.concurrent.forkjoin;
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