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Maple is the only technical computing system that allows you to take advantage of multithreading in your own programs. The Maple programming language offers direct access to launching and controlling threads. In addition, Maple also offers a task-based programming model that simplifies thread management. Writing parallel algorithms using the Task Programming Model reduces and removes many of the difficulties associated with standard threaded programming.
Thread performance has been significantly enhanced in Maple 15, and a number of important additions to the task-based API allow you to write parallel programs more effectively and to take advantage of all cores on your machine. These additions will simply your code for a number of common situations.
The new Threads[Sleep] function allows you to pause a thread for a fixed duration. For example:
 
The Threads[Task][Start] function has been enhanced to accepts as arguments a specification of child tasks, similar to Threads[Task][Continue]. This argument sequence creates a continuation task and child tasks, then waits for the continuation task to return. This syntax can be used to replace cases where the root task is simply a call to Continue.
Here is an example of using this new functionality to compute a convex hull. Given X, a set of points in 2-D, the convex hull is the minimum set of points that define a polygon containing all the points of X. If you imagine the points as pegs on a board, you can find the convex hull by surrounding the pegs by a loop of string and then tightening the string until there is no more slack.
By adding parallelism, which was relatively simple to do, to the standard quick hull algorithm for computing convex hulls, you can see substantial speedups:
You can find the complete code for running this example here
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