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Distributed Arrays

Analyze big data sets in parallel using distributed arrays and simultaneous execution.

Parallel Computing Toolbox™ supports distributed arrays to partition large arrays across multiple MATLAB® workers. Simultaneous execution is supported by the single program multiple data (spmd) language construct to facilitate communication between workers. You can use distributed arrays in Parallel Computing Toolbox to run big data applications using the combined memory of your cluster.

Functions

distributed Create distributed array from data in client workspace
gather Transfer distributed array or gpuArray to local workspace
spmd Execute code in parallel on workers of parallel pool
Composite Create Composite object
parallel.pool.Constant Build parallel.pool.Constant from data or function handle
codistributed Create codistributed array from replicated local data
parpool Create parallel pool on cluster
delete (Pool) Shut down parallel pool
redistribute Redistribute codistributed array with another distribution scheme
codistributed.build Create codistributed array from distributed data
for for-loop over distributed range
getLocalPart Local portion of codistributed array
globalIndices Global indices for local part of codistributed array
gop Global operation across all workers

Classes

distributed Access elements of distributed arrays from client
codistributed Access elements of arrays distributed among workers in parallel pool
Composite Access nondistributed variables on multiple workers from client
codistributor1d 1-D distribution scheme for codistributed array
codistributor2dbc 2-D block-cyclic distribution scheme for codistributed array
parallel.Pool Access parallel pool

Examples and How To

Distributing Arrays

Use datastore or distributed to create distributed arrays and partition the data among your workers

Using MATLAB Functions on Distributed Arrays

MATLAB functions that operate on codistributed arrays

Run Single Programs on Multiple Data Sets

Use spmd statements to run the same code on multiple datasets and control codistributed arrays

Access Worker Variables with Composites

Composite objects in the MATLAB client session let you directly access data values on the workers.

Concepts

Run Code on Parallel Pools

Learn about starting and stopping parallel pools, pool size, and cluster selection.

Specify Your Parallel Preferences

Specify your preferences, and automatically create a parallel pool.

Nondistributed Versus Distributed Arrays

Describes the various types of arrays used in communicating jobs, including pmode

Working with Codistributed Arrays

Describes how to use codistributed arrays for calculation

Looping Over a Distributed Range (for-drange)

Describes how to program a for-loop with codistributed arrays

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