After you integrate MATLAB® Parallel Server™ with your existing cluster infrastructure, you can run parallel code in your cluster. If you need to set up your cluster, see Get Started with MATLAB Parallel Server. Then, to learn more about cluster workflows, try the examples in this section.
Scale Up from Desktop to Cluster (Parallel Computing Toolbox)
This example shows how to develop your parallel MATLAB® code on your local machine and scale up to a cluster.
Plot During Parameter Sweep with parfor (Parallel Computing Toolbox)
This example shows how to perform a parameter sweep in parallel and plot progress during parallel computations.
Scale Up parfor-Loops to Cluster and Cloud (Parallel Computing Toolbox)
parfor-loops on your desktop, and scale up to a
cluster without changing your code.
Clusters and Clouds (Parallel Computing Toolbox)
Discover cluster resources, and work with cluster profiles
Choose a Parallel Computing Solution (Parallel Computing Toolbox)
Discover the most important functionalities offered by MATLAB and Parallel Computing Toolbox™ to solve your parallel computing problem.
Launch MATLAB Parallel Server in AWS using a reference architecture.
Launch MATLAB Parallel Server in AWS using a reference architecture for AWS Batch.
Launch MATLAB Parallel Server in Microsoft® Azure® using a reference architecture.
Launch MATLAB Parallel Server in Microsoft Azure from the Microsoft Azure Marketplace.
Set up a network license for use with MATLAB Parallel Server running in the Cloud.
Get Started with Parallel Computing Toolbox (Parallel Computing Toolbox)
Parallel Computing Toolbox lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—enable you to parallelize MATLAB applications without CUDA or MPI programming. The toolbox lets you use parallel-enabled functions in MATLAB and other toolboxes. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel. Programs and models can run in both interactive and batch modes.