Run Code on Clusters and Cloud Platforms
Scale up and run computationally intensive code in your existing
cluster
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 Installation. Then, discover your cluster from any MATLAB session and try parallel computing and deep learning workflows.
Topics
Client Setup
- Discover Clusters and Use Cluster Profiles (Parallel Computing Toolbox)
Find out how to work with cluster profiles and discover cloud clusters.
Parallel Computing Basics
- Scale Up from Desktop to Cluster (Parallel Computing Toolbox)
Develop your parallel MATLAB® code on your local machine and scale up to a cluster. - 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. - Plot During Parameter Sweep with parfor (Parallel Computing Toolbox)
Perform a parameter sweep in parallel and plot progress during parallel computations. - Scale Up parfor-Loops to Cluster and Cloud (Parallel Computing Toolbox)
Developparfor-loops on your desktop, and scale up to a cluster without changing your code.
Deep Learning with Parallel Computing
- Train Deep Learning Networks in Parallel (Deep Learning Toolbox)
This example shows how to run multiple deep learning experiments on your local machine. - Scale Up Deep Learning in Parallel, on GPUs, and in the Cloud (Deep Learning Toolbox)
Explore options for deep learning with MATLAB in parallel and using multiple GPUs, locally or in the cloud. - Use parfor to Train Multiple Deep Learning Networks (Deep Learning Toolbox)
This example shows how to use aparforloop to perform a parameter sweep on a training option.
Related Information
- Get Started with Parallel Computing Toolbox (Parallel Computing Toolbox)
- Reduce Time to Results with MATLAB Using Parallel Computing
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