Parallel Computing Toolbox

Perform parallel computations on multicore computers, GPUs, and

computer clusters

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 the basics of Parallel Computing Toolbox

Choose a parallel computing solution

Use parallel processing by running parfor on

workers in a parallel pool

Evaluate functions in the background using parfeval

Analyze big data sets in parallel using distributed

arrays, tall arrays, datastores, or mapreduce,

on Spark® and Hadoop® clusters

Offload execution of functions to run in the background

Accelerate your code by running it on a GPU

Discover cluster resources, and work with cluster profiles

Improve performance of parallel code