Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—let you parallelize MATLAB® applications without CUDA or MPI programming. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel.
The toolbox provides twelve workers (MATLAB computational engines) to execute applications locally on a multicore desktop. Without changing the code, you can run the same application on a computer cluster or a grid computing service (using MATLAB Distributed Computing Server™). You can run parallel applications interactively or in batch.
Parallel for-loops (parfor) for running task-parallel algorithms on multiple processors
Support for CUDA-enabled NVIDIA GPUs
Ability to run twelve workers locally on a multicore desktop
Computer cluster and grid support (with MATLAB Distributed Computing Server)
Interactive and batch execution of parallel applications
Distributed arrays and spmd (single-program-multiple-data) for large dataset handling and data-parallel algorithms