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.
Key Features
Support for data-parallel and task-parallel application development
Ability to Annotate code segments with parfor (parallel for-loops) and spmd (single program multiple data) for implementing task- and data-parallel algorithms
High-level constructs such as distributed arrays, parallel algorithms, and message-passing functions for processing large data sets on multiple processors
Ability to run eight workers locally on a multicore desktop
Integration with MATLAB Distributed Computing Server for Cluster-based applications that use any scheduler or any number of workers
Interactive and batch Execution modes
