Parallel Computing Toolbox

Scaling Up to Clusters, Grids, and Clouds Using MATLAB Distributed Computing Server

Parallel Computing Toolbox provides the ability to use up to twelve workers to execute parallel applications locally on a multicore computer. Using the toolbox in conjunction with MATLAB Distributed Computing Server, you can run applications that use more workers on large-scale computing resources, such as computer clusters or grid and cloud computing services. The server also supports both interactive and batch workflows.

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.

Integrating Products into Your Computing Environment

MATLAB Distributed Computing Server provides a job manager and directly supports several third-party schedulers, such as Microsoft^® Windows^® HPC Server, TORQUE, Altair PBS Pro^®, and Platform LSF^®. Using the Configurations Manager in the toolbox, you can maintain named configurations that describe scheduler type, path settings, and cluster-usage policies. Switching between clusters or schedulers typically requires changing the configuration name only.

Administrators manage only the server license on the cluster rather than separate toolbox and blockset licenses for every cluster user. When an application is executed on a computer cluster, MATLAB Distributed Computing Server dynamically enables the required products based on the products that a user is licensed to use on the desktop.