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—enable you to parallelize MATLAB® applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.
The toolbox lets you use the full processing power of multicore desktops by executing applications on workers (MATLAB computational engines) that run locally. Without changing the code, you can run the same applications on clusters or clouds (using MATLAB Parallel Server™). You can also use the toolbox with MATLAB Parallel Server to execute matrix calculations that are too large to fit into the memory of a single machine.
Learn about MATLAB and Parallel Computing Toolbox
Discover the most important functionalities offered by MATLAB and Parallel Computing Toolbox to solve your parallel computing problem.
Take advantage of parallel computing resources without requiring any extra coding.
Convert a slow
for-loop into a
This example shows how to develop your parallel MATLAB® code on your local machine and scale up to a cluster.
Use batch to offload work from your MATLAB session to run in the background.
Hundreds of functions in MATLAB and other toolboxes run automatically on GPU if you supply a
Overview of parallel computing with MathWorks products