Learn more about Parallel Computing Toolbox

Introduction

A parallel job consists of only a single task that runs simultaneously on several workers, usually with different data. More specifically, the task is duplicated on each worker, so each worker can perform the task on a different set of data, or on a particular segment of a large data set. The workers can communicate with each other as each executes its task. In this configuration, workers are referred to as labs.

In principle, creating and running parallel jobs is similar to programming distributed jobs:

1. Find a scheduler.

2. Create a parallel job.

3. Create a task.

4. Submit the job for running.

5. Retrieve the results.

The differences between distributed jobs and parallel jobs are summarized in the following table.

Distributed Job	Parallel Job
MATLAB sessions, called workers, perform the tasks but do not communicate with each other.	MATLAB sessions, called labs, can communicate with each other during the running of their tasks.
You define any number of tasks in a job.	You define only one task in a job. Duplicates of that task run on all labs running the parallel job.
Tasks need not run simultaneously. Tasks are distributed to workers as the workers become available, so a worker can perform several of the tasks in a job.	Tasks run simultaneously, so you can run the job only on as many labs as are available at run time. The start of the job might be delayed until the required number of labs is available.

A parallel job has only one task that runs simultaneously on every lab. The function that the task runs can take advantage of a lab's awareness of how many labs are running the job, which lab this is among those running the job, and the features that allow labs to communicate with each other.

Programming Parallel Jobs

Using a Supported Scheduler

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