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Parallel Computing Toolbox 4.1

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“ Perform parallel computations on multicore computers and computer clusters . ”

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Presentation

You can use the toolbox to execute applications on a single multicore or multiprocessor desktop. Without changing the code, you can run the same application on a computer cluster (using MATLAB Distributed Computing Server™). Parallel MATLAB applications can be distributed as executables or shared libraries (built using MATLAB Compiler™) that can access MATLAB Distributed Computing Server.

Support for data-parallel and task-parallel application development

Ability to annotate code segments with parfor (parallel for-loops) and spmd (single program multiple data) for implementing task- and data-parallel algorithms

High-level constructs such as distributed arrays, parallel algorithms, and message-passing functions for processing large data sets on multiple processors

Ability to run eight workers locally on a multicore desktop

Integration with MATLAB Distributed Computing Server for cluster-based applications that use any scheduler or any number of workers

Interactive and batch execution modes

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