Parallel for-Loops (parfor)

Use parallel processing by running parfor on workers in a parallel pool

Parallel Computing Toolbox™ supports interactive parallel computing and enables you to accelerate your workflow by running on multiple workers in a parallel pool. Use parfor to execute for-loop iterations in parallel on workers in a parallel pool. When you have profiled your code and identified slow for-loops, try parfor to increase your throughput. Develop parfor-loops on your desktop and scale up to a cluster without changing your code.

Functions

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parforExecute for-loop iterations in parallel on workers
parforOptionsOptions for parfor, such as partitioning iterations
parpoolCreate parallel pool on cluster
parfevalExecute function asynchronously on parallel pool worker
ticBytesStart counting bytes transferred within parallel pool
tocBytesRead how many bytes have been transferred since calling ticBytes
sendSend data from worker to client using a data queue
afterEachDefine a function to call when new data is received on a DataQueue
parallel.PoolAccess parallel pool
parallel.pool.DataQueueClass that enables sending and listening for data between client and workers

Topics

Getting Started with parfor

Decide When to Use parfor

Discover basic concepts of a parfor-loop, and decide when to use it.

Convert for-Loops Into parfor-Loops

Diagnose and fix common parfor problems.

Ensure That parfor-Loop Iterations are Independent

Unlike a for-loop, parfor-loop Iterations have no guaranteed order.

Nested parfor and for-Loops and Other parfor Requirements

Learn how to deal with parallel nested loops.

Troubleshoot Variables in parfor-Loops

Discover variable requirements and classification in parfor-loops.

Running parfor-Loops

Interactively Run a Loop in Parallel Using parfor

Convert a slow for-loop into a faster parfor-loop.

Improve parfor Performance

Create arrays inside or outside parfor-loops to speed up code.

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.

Use Objects and Handles in parfor-Loops

Discover how to use objects, handles, and sliced variables in parfor-loops.

Ensure Transparency in parfor-Loops or spmd Statements

All references to variables in parfor-loops must be visible in the body of the program.

Scale Up parfor-Loops to Cluster and Cloud

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

Use parfor-Loops for Reduction Assignments

You can use parfor-loops to calculate cumulative values that are updated by each iteration.

Repeat Random Numbers in parfor-Loops

Control random number generation in parfor-loops by assigning a particular substream for each iteration.

Deep Learning

Use parfor to Train Multiple Deep Learning Networks

This example shows how to use a parfor loop to perform a parameter sweep on a training option.

Featured Examples