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Actualizado 15 ago 2023

Parallel Computing Toolbox plugin for MATLAB Parallel Server with AWS Batch

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MATLAB® Parallel Computing Toolbox™ provides the Generic cluster type for submitting MATLAB jobs to a cluster running a third-party scheduler. Generic uses a set of plugin scripts to define how your machine running MATLAB or Simulink® communicates with your scheduler. You can customize the plugin scripts to configure how MATLAB interacts with the scheduler to best suit your cluster's setup and to support custom submission options.

This repository contains MATLAB code files and shell scripts that you can use to submit jobs from a MATLAB or Simulink session running on Windows®, Linux®, or macOS to AWS Batch.

Products Required

Usage Notes

MATLAB Parallel Server with AWS Batch does not support communicating jobs. To learn more about communicating jobs, see Program Communicating Jobs.

Setup Instructions

Before proceeding, ensure that the above required products are installed.

Download or Clone this Repository

To download a zip file of this repository, at the top of this repository page, select Code > Download ZIP. Alternatively, to clone this repository to your computer with git installed, run the following command on your operating system's command line:

git clone https://github.com/mathworks/matlab-parallel-aws-batch-plugin

You can execute a system command from the MATLAB command line by adding a ! before the command.

Launch the Reference Architecture in AWS Batch

The "MATLAB Parallel Server with AWS Batch" reference architecture must be running in your AWS account. If you are an end user, contact your administrator to see if the reference architecture has already been launched. If you need to launch the reference architecture yourself, see the GitHub repository for MATLAB Parallel Server with AWS Batch.

Configure Your AWS Credentials

Configure your machine with your AWS Credentials using the AWS Command Line Interface tool. Alternatively, you can set up your credentials by setting the following environment variables:

Environment variable Description
AWS_ACCESS_KEY_ID Specifies an AWS access key associated with an IAM (Identity and Access Management) user or role.
AWS_SECRET_ACCESS_KEY Specifies the secret key associated with the access key. This is essentially the "password" for the access key.
AWS_SESSION_TOKEN Specifies the session token value. Required if you are using temporary security credentials.
AWS_DEFAULT_REGION Specifies the AWS Region to send the request to. The value of this environment variable is typically determined automatically but you may wish to set it manually.

If you do not know your AWS Credentials, contact your administrator. You can set the environment variables in your current MATLAB session using setenv as follows:


Cluster Discovery

Since version R2023a, MATLAB can discover clusters running third-party schedulers such as AWS Batch. As a cluster admin, you can create a configuration file that describes how to configure the Parallel Computing Toolbox on the user's machine to submit MATLAB jobs to the cluster. The cluster configuration file is a plain text file with the extension .conf containing key-value pairs that describe the cluster configuration information. The MATLAB client will use the cluster configuration file to create a cluster profile for the user who discovers the cluster. Therefore, users will not need to follow the instructions in the sections below. You can find an example of a cluster configuration file in discover/example.conf. For full details on how to make a cluster running a third-party scheduler discoverable, see the documentation for Configure for Third-Party Scheduler Cluster Discovery.

Create a Cluster Profile in MATLAB

You can create a cluster profile by using either the Cluster Profile Manager or the MATLAB command line.

To open the Cluster Profile Manager, on the Home tab, in the Environment section, select Parallel > Create and Manage Clusters. Within the Cluster Profile Manager, select Add Cluster Profile > Generic from the menu to create a new Generic cluster profile.

Alternatively, for a command line workflow without using graphical user interfaces, create a new Generic cluster object by running:

c = parallel.cluster.Generic;

Configure Cluster Properties

The table below gives the minimum properties required for Generic to work correctly. For a full list of cluster properties, see the documentation for parallel.Cluster.

Property Value
JobStorageLocation Where job data is stored by your machine.
NumWorkers Number of workers your license allows.
ClusterMatlabRoot '/usr/local/matlab'
OperatingSystem 'unix'
HasSharedFilesystem false
PluginScriptsLocation Full path to the folder containing this file.

In the Cluster Profile Manager, set each property value in the boxes provided. Alternatively, at the command line, set each property on the cluster object using dot notation:

c.JobStorageLocation = 'C:\MatlabJobs';
% etc.

At the command line, you can also set properties at the same time you create the Generic cluster object, by specifying name-value pairs in the constructor:

c = parallel.cluster.Generic( ...
    'JobStorageLocation', 'C:\MatlabJobs', ...
    'NumWorkers', 20, ...
    'ClusterMatlabRoot', '/usr/local/matlab', ...
    'OperatingSystem', 'unix', ...
    'HasSharedFileSystem', false, ...
    'PluginScriptsLocation', 'C:\MatlabAwsBatchPlugin\shared');

Configure AdditionalProperties

You can use AdditionalProperties as a way of modifying the behaviour of Generic without having to edit the plugin scripts. By modifying the plugins, you can add support for your own custom AdditionalProperties. The following AdditionalProperties are required:

Property Name Description
IndependentJobDefinition The AWS Batch job definition for independent jobs.
JobQueue The AWS Batch job queue of the cluster.
S3Bucket The Amazon S3 bucket for data transfer between the client and workers.

The following additional property is optional:

Property Name Description
LicenseServer The port and hostname of a machine running a Network License Manager in the format port@hostname.

If you have launched the "MATLAB Parallel Server with AWS Batch" reference architecture yourself, this information can be found in the AWS CloudFormation console by navigating to the output view of the stack. If you are an end-user, contact your administrator for this information.

In the Cluster Profile Manager, add new AdditionalProperties by clicking Add under the table of AdditionalProperties. On the command line, use dot notation to add new fields:

c.AdditionalProperties.IndependentJobDefinition = '<Job definition>';

Save Your New Profile

In the Cluster Profile Manager, click Done. If creating the cluster on the command line, run:

saveAsProfile(c, "myAwsBatchCluster");

Your cluster profile is now ready to use.

Validate the Cluster Profile

Cluster validation submits one of each type of job to test the cluster profile has been configured correctly. In the Cluster Profile Manager, click the Validate button. The Cluster connection test (parcluster) and Job test (createJob) stages should pass successfully. The remaining validation stages will not pass as communicating jobs are not supported. If you make a change to a cluster profile, you can rerun cluster validation to ensure there are no errors. You do not need to validate each time you use the profile or each time you start MATLAB.


First create a cluster object using your profile:

c = parcluster("myAwsBatchCluster")

Submit Work for Batch Processing

The batch command runs a MATLAB script or function on a worker on the cluster. For more information about batch processing, see the documentation for the batch command.

% Create and submit a job to the cluster
job = batch( ...
    c, ... % cluster object created using parcluster
    @sqrt, ... % function/script to run
    1, ... % number of output arguments
    {[64 100]}); % input arguments

% Your MATLAB session is now available to do other work, such
% as create and submit more jobs to the cluster. You can also
% shut down your MATLAB session and come back later - the work
% will continue running on the cluster. Once you've recreated
% the cluster object using parcluster, you can view existing
% jobs using the Jobs property on the cluster object.

% Wait for the job to complete. If the job is already complete,
% this will return immediately.

% Retrieve the output arguments for each task. For this example,
% results will be a 1x1 cell array containing the vector [8 10].
results = fetchOutputs(job)


The license is available in the license.txt file in this repository.

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If you require assistance or have a request for additional features or capabilities, contact MathWorks Technical Support at https://www.mathworks.com/support/contact_us.html.

Copyright 2022-2023 The MathWorks, Inc.

Citar como

MathWorks Parallel Computing Toolbox Team (2024). Parallel Computing Toolbox Plugin for AWS Batch (https://github.com/mathworks/matlab-parallel-awsbatch-plugin/releases/tag/v2.0.1), GitHub. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2023a
Compatible con cualquier versión desde R2019b
Compatibilidad con las plataformas
Windows macOS Linux

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Versión Publicado Notas de la versión

See release notes for this release on GitHub: https://github.com/mathworks/matlab-parallel-awsbatch-plugin/releases/tag/v2.0.1

See release notes for this release on GitHub: https://github.com/mathworks/matlab-parallel-awsbatch-plugin/releases/tag/v2.0.0


Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.