Parallel Computing Toolbox
Product Description
- Parallel Computing Toolbox Key Features
- Programming Parallel Applications
- Using Built-In Parallel Algorithms in Other MathWorks Products
- Speeding Up Task-Parallel Applications
- Speeding Up MATLAB Computations with GPUs
- Scaling Up to Clusters, Grids, and Clouds Using MATLAB Distributed Computing Server
- Implementing Data-Parallel Applications using the Toolbox and MATLAB Distributed Computing Server
- Running Parallel Applications Interactively and as Batch Jobs
Running Parallel Applications Interactively and as Batch Jobs
You can execute parallel applications interactively and in batch using Parallel Computing Toolbox. Using the matlabpool command, you can connect your MATLAB session to a pool of MATLAB workers that can run either locally on your desktop (using the toolbox) or on a computer cluster (using MATLAB Distributed Computing Server) to setup a dedicated interactive parallel execution environment. You can execute parallel applications from the MATLAB prompt on these workers and retrieve results immediately as computations finish, just as you would in any MATLAB session.
Running applications interactively is suitable when execution time is relatively short. When your applications need to run for a long time, you can use the toolbox to set them up to run as batch jobs. This enables you to free your MATLAB session for other activities while you execute large MATLAB and Simulink applications.
While your application executes in batch, you can shut down your MATLAB session and retrieve results later. The toolbox provides several mechanisms to manage offline execution of parallel programs, such as the batch function and job and task objects. Both the batch function and the job and task objects can be used to offload the execution of serial MATLAB and Simulink applications from a desktop MATLAB session.

Free Parallel Computing Interactive Kit
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