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Clusters and Clouds

Discover cluster resources and work with cluster profiles

If your computing task is too big or too slow for your local computer, you can offload your calculation to a cluster onsite or in the cloud to run your MATLAB® code with minimal changes. Try Parallel > Discover Clusters in the MATLAB toolstrip to find out if you already have a cluster available.

If you already have a cluster with a scheduler, you can integrate MATLAB with it using MATLAB Distributed Computing Server™. Alternatively, if you do not have an existing scheduler, then MATLAB Distributed Computing Server provides MATLAB Job Scheduler (MJS) .

Functions

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parclusterCreate cluster object
parpoolCreate parallel pool on cluster
gcpGet current parallel pool
shutdown Shut down cloud cluster
startStart cloud cluster
wait (cluster)Wait for cloud cluster to change state
parallel.defaultClusterProfileExamine or set default cluster profile
parallel.exportProfileExport one or more profiles to file
parallel.importProfileImport cluster profiles from file
saveProfileSave modified cluster properties to its current profile
saveAsProfileSave cluster properties to specified profile
pctconfigConfigure settings for Parallel Computing Toolbox client session

Classes

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parallel.PoolAccess parallel pool
parallel.ClusterAccess cluster properties and behaviors
pctRunOnAllRun command on client and all workers in parallel pool

Examples and How To

Discover Clusters and Use Cluster Profiles

Find out how to work with cluster profiles and discover cloud clusters running on Amazon EC2.

MATLAB Parallel Cloud

Run your application on workers in MATLAB Parallel Cloud™

Scale Up parfor-Loops to Cluster and Cloud

Develop parfor-loops on your desktop, and scale up to a cluster without changing your code.

Concepts

Specify Your Parallel Preferences

Specify your preferences, and automatically create a parallel pool.

Integration Scripts for Generic Schedulers

How to use integration scripts to set up generic schedulers.

Related Information

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