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Clusters and Clouds

Discover cluster resources and work with cluster profiles

If your computing task is too big for your local computer, you may want to offload your calculation to networked nodes on a computer cluster. This may be a local cluster or a cluster in the cloud. Changes required to run your MATLAB® code on a cluster are often minimal. Use the MATLAB Job Scheduler (MJS) Profile to exploit computer clusters that have MATLAB Distributed Computing Server™ installed.

Functions

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

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.

Program Independent Jobs for a Generic Scheduler

Programming an independent job using a generic scheduler interface to distribute the tasks

Program Communicating Jobs for a Generic Scheduler

How to program a communicating job using the generic scheduler interface

Related Information

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