Parallel Computing Toolbox 4.0

Product Description

• Parallel Computing Toolbox Key Features
• Programming Parallel Applications in MATLAB
• Working in an Interactive Parallel Environment
• Working in Batch Environments
• Scaling to a Cluster Using MATLAB Distributed Computing Server

Scaling to a Cluster Using MATLAB Distributed Computing Server

Parallel Computing Toolbox provides the ability to use up to four local workers on a multicore or multiprocessor computer using a single toolbox license. When used together with MATLAB Distributed Computing Server, you can scale up your application to use any number of workers running on any number of computers. MATLAB Distributed Computing Server also supports both interactive and batch workflows. In addition, MATLAB applications that use Parallel Computing Toolbox functions can be built into standalone executables and shared software components using MATLAB Compiler, for royalty-free distribution. These executables and libraries can connect to MATLAB Distributed Computing Server workers and perform MATLAB computations on a computer cluster.

MATLAB Distributed Computing Server supports several schedulers: the MathWorks job manager (provided with the product) or any other third-party scheduler such as Platform LSF®, Microsoft® Windows® Compute Cluster Server, Altair PBS Pro®, and TORQUE.

Using the Configurations Manager in the toolbox, you can maintain named settings such as scheduler type, path settings, and cluster usage policies. Switching between clusters or schedulers typically requires changing the configuration name only.

MATLAB Distributed Computing Server dynamically enables the required licenses on the cluster based on the user’s profile when an application runs. As a result, administrators need to manage only a server license on the cluster rather than separate toolbox and blockset licenses on the cluster for every cluster user.

Running a gene regulation model on a cluster using MATLAB Distributed Computing Server. The server enables applications developed using Parallel Computing Toolbox to harness computer clusters for large problems. Compiled parallel MATLAB applications can also use the server. Click on image to see enlarged view.