Note: This page has been translated by MathWorks. Click here to see

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

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.

**What Is Parallel Computing?**

Learn about MATLAB and Parallel Computing Toolbox

**Choose a Parallel Computing Solution**

Discover the most important functionalities offered by MATLAB and Parallel Computing Toolbox to solve your parallel computing problem.

**Run MATLAB Functions with Automatic Parallel Support**

Take advantage of parallel computing resources without requiring any extra coding.

**Interactively Run a Loop in Parallel Using parfor**

Convert a slow

`for`

-loop into a faster`parfor`

-loop.**Scale up from Desktop to Cluster**

This example shows how to develop your parallel MATLAB® code on your local machine and scale up to a cluster.

**Run Batch Parallel Jobs**

Use batch to offload work from your MATLAB session to run in the background.

**Run MATLAB Functions on a GPU**

Hundreds of functions in MATLAB and other toolboxes run automatically on GPU if you supply a

`gpuArray`

argument.

**Parallel Computing Support in MathWorks Products**

Overview of parallel computing with MathWorks products

**Glossary**

**Parallel Computing Toolbox Overview**

Scale up your computations in parallel on multicore computers, GPUs, and
clusters

**Introduction to GPU Computing with MATLAB**

Accelerate your MATLAB applications with GPUs and built-in GPU support