Grid Computing (Parallel Distributed Computing)

Distributed systems offer fantastic gains when it comes to solving large-scale problems. By sharing the computation load, you can solve problems too large for a single computer to handle, or solve problems in a fraction of the time it would take with a single computer. The Grid Computing Toolbox has been streamlined for Maple 15, making it easy to create and test parallel distributed programs. New features include a simplified local grid setup, flexible argument passing, and an extended API. Compatible with Maple 15 Local Grid API Maple 15 includes the ability to easily set up multi-process computations on a single computer. The Maple Grid Computing Toolbox extends this power to multi-machine or cluster parallelism. The two versions are fully compatible, so that an algorithm can be created and fully tested using the local implementation inside Maple, and then deployed to the full cluster using the toolbox, without changes to the algorithm. Flexible Argument Passing The Launch command can now process multi-argument procedures and automatically pass those parameters to each of the nodes in the grid. This avoids the need to work with global data referenced by the 'exports' option. Getting data to each node can be done in two ways using the Launch command. • Arguments to the called procedure can be passed as arguments to the Launch command. • Other data can be specified using the 'imports' option to Launch Also, once the computation has been started, Send and Receive can be used for passing chunks of data to each individual node.