Parallel Computing Toolbox

Key Features

  • Parallel for-loops (parfor) for running task-parallel algorithms on multiple processors
  • Support for CUDA-enabled NVIDIA GPUs
  • Full use of multicore processors on the desktop via workers that run locally
  • Computer cluster and grid support (with MATLAB Distributed Computing Server)
  • Interactive and batch execution of parallel applications
  • Distributed arrays and single program multiple data (spmd) construct for large dataset handling and data-parallel algorithms
Parallel Computing with MATLAB.

Parallel computing with MATLAB. You can use Parallel Computing Toolbox to run applications on a multicore desktop with local workers available in the toolbox, take advantage of GPUs, and scale up to a cluster (with MATLAB Distributed Computing Server).

Next: Programming Parallel Applications

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