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

expand all

Functions and Classes

`parfor`	Execute `for`-loop iterations in parallel on workers
`parforOptions`	Options set for `parfor`
`parpool`	Create parallel pool on cluster
`parfeval`	Run function on parallel pool worker
`ticBytes`	Start counting bytes transferred within parallel pool
`tocBytes`	Read how many bytes have been transferred since calling `ticBytes`
`send`	Send data between clients and workers using a data queue
`afterEach`	Define a function to call when new data is received on a data queue
`parallel.Pool`	Parallel pool of workers
`parallel.pool.DataQueue`	Send and listen 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 Loops in Parallel Using parfor
Convert a for-loop into a scalable 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.
Save Variables in parfor-Loops
This example shows how to use the save function in a parfor-loop to save one or more variables to a file. (Since R2024a)
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.
Use parfor to Speed Up Monte-Carlo Code
This example shows how to speed up Monte-Carlo code by using parfor-loops.
Interactively Import and Process Data in Parallel
This example shows how to import and process data simultaneously in an interactive parallel pool. (Since R2023b)

Deep Learning

Use parfor to Train Multiple Deep Learning Networks (Deep Learning Toolbox)
This example shows how to use a parfor loop to perform a parameter sweep on a training option.

Featured Examples

Plot During Parameter Sweep with parfor

Perform a parameter sweep in parallel and plot progress during parallel computations.

Open Live Script

Scale Up from Desktop to Cluster

Develop your parallel MATLAB® code on your local machine and scale up to a cluster.

Open Live Script

Use parfor to Speed Up Monte-Carlo Code

Speed up Monte-Carlo code by using parfor-loops. Monte-Carlo methods are found in many fields, including physics, mathematics, biology, and finance. Monte-Carlo methods involve executing a function many times with randomly distributed inputs. With Parallel Computing Toolbox, you can replace a for-loop with a parfor-loop to easily speed up code.

Open Live Script

Parallel for-Loops (parfor)