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Parallel Computing Toolbox 4.1

Other software

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