Parallel Computing Toolbox™ 3.3

Product Description

• Parallel Computing Toolbox Key Features
• Programming Task-Parallel Applications
• Programming Data-Parallel Applications
• Working in an Interactive Parallel Environment
• Working in a Batch Environment
• Scaling to a Cluster Using MATLAB® Distributed Computing Server™

Introduction

Parallel Computing Toolbox™ enables you to use MATLAB® and Simulink® to harness multiprocessing hardware for solving computationally and data-intensive problems. The Parallel Computing Toolbox software extends the MATLAB language with high-level parallel processing constructs such as parallel for-loops, distributed arrays, parallel numerical algorithms, and message-passing functions that let you exploit data and task parallelism in your applications. You can transition from serial MATLAB programs to parallel MATLAB programs without making significant changes to existing code or learning a low-level parallel language.

Parallel Computing Toolbox lets you execute programs on a single multicore or multiprocessor workstation. When used together with MATLAB® Distributed Computing Server™, you can execute programs on a computer cluster. Both interactive and batch execution modes are supported.

Key Features

• Support for data-parallel and task-parallel application development
• Parallel for-loops, distributed arrays, parallel algorithms, and message-passing functions
• Ability to run four workers locally on a multiprocessor 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

Developing parallel applications with Parallel Computing Toolbox™. The toolbox enables application prototyping on the desktop with up to four local workers (left), and, with MATLAB® Distributed Computing Server™ (right), applications can be scaled to multiple computers on a cluster. Click on image to see enlarged view.