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Parallel Computing Toolbox 4.3

Perform parallel computations on multicore computers and computer clusters


Parallel Computing Toolbox - Main Image

Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using MATLAB® and Simulink® on multicore and multiprocessor computers. Parallel processing constructs such as parallel for-loops and code blocks, distributed arrays, parallel numerical algorithms, and message-passing functions let you implement task- and data-parallel algorithms in MATLAB at a high level without programming for specific hardware and network architectures. As a result, converting serial MATLAB applications to parallel MATLAB applications requires few code modifications and no programming in a low-level language. You can run your applications interactively or offline, in batch environments.

You can use the toolbox to execute applications on a single multicore or multiprocessor desktop. Without changing the code, you can run the same application on a computer cluster (using MATLAB Distributed Computing Server™). Parallel MATLAB applications can be distributed as executables or shared libraries (built using MATLAB Compiler™) that can access MATLAB Distributed Computing Server.

Built-in Parallel Computing Support in MathWorks Productsnew

Parallel Computing with MATLAB on Amazon Elastic Compute Cloud (EC2)


Trials available for Parallel Computing Toolbox
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Argonne National Laboratory PSAT Toolkit

"With distributed computing, we went from running one set of simulations in two weeks to only one day."
- Sylvain Pagerit, Argonne