MATLAB® Parallel Server™ with AWS® Batch is a solution for batch processing MATLAB jobs using Amazon® Web Services (AWS). This repository helps you automate the process of launching an AWS Batch cluster in your AWS account.
AWS Batch is a service for running batch computing jobs on AWS. AWS Batch dynamically provisions, manages, monitors, and terminates Amazon EC2® instances based on the volume and resource requirements of the submitted jobs. Both On-Demand and Spot EC2 instances are supported. AWS Batch jobs run as containerized applications on Elastic Container Service (ECS) container instances. For more information about ECS containers, see What is Amazon Elastic Container Service?.
For information about the architecture of this solution, see Learn About Cluster Architecture.
MATLAB Parallel Server with AWS Batch does not support communicating jobs. To run communicating jobs, you can run MATLAB Parallel Server in AWS using the built-in MATLAB Job Scheduler instead of AWS Batch using this GitHub® repository: MATLAB Parallel Server on AWS. For a simpler but less customizable method of launching a MATLAB Parallel Server cluster in AWS, try MathWorks Cloud Center instead.
Before starting, you must have the following:
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MATLAB Parallel Server license. For more information on how to configure your license for cloud use, see MATLAB Parallel Server on the Cloud.
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MATLAB and Parallel Computing Toolbox™ on your desktop.
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An AWS account with required permissions. To see what is required, look at the example policy. For more information about the services used, see Learn About Cluster Architecture.
You are responsible for the cost of the AWS services used when you create cloud resources using this repository. Resource settings, such as instance type, affect the cost of deployment. For cost estimates, see the pricing pages for each AWS service you use. Prices are subject to change.
To view instructions for deploying the MATLAB Parallel Server with AWS Batch reference architecture, select a MATLAB release:
| Release |
|---|
| R2024b |
| R2024a |
| R2023b |
| R2023a |
| R2022b |
| R2022a |
| R2021b |
| R2021a |
| R2020b |
| R2020a |
| R2019b |
This diagram illustrates the cluster architecture and operation of MATLAB Parallel Server with AWS Batch. When you use the AWS CloudFormation templates in this repository, it creates the AWS Batch Cluster and the following resources. For more information about each resource, see the AWS CloudFormation template reference.
Figure 1: Cluster Architecture
- Job Definition (AWS::Batch::JobDefinition)
The job definition specifies how a job is run. It defines the following:
- The Docker container image to use.
- The number of virtual CPUS (vCPUS), GPUs, and the amount of memory a job requires.
- Where to mount the data volume containing the MATLAB installation.
- Compute environment (AWS::Batch::ComputeEnvironment)
The compute environment used to run jobs. It defines the following:
- The EC2 pricing model to use (On-Demand or Spot).
- The launch template to use for EC2 instances.
- The EC2 instance types to use.
- The maximum number of vCPUs that can run simultaneously.
- That the cluster scales down to zero vCPUs when no jobs are in the queue.
- Job Queue (AWS::Batch::JobQueue) The job queue to which jobs are submitted. Jobs submitted to the queue run in the defined compute environment.
- Amazon S3™ Bucket for data transfer (AWS::S3::Bucket) The S3 bucket used for data transfer between the MATLAB client and the MATLAB workers running in AWS Batch.
- Launch template (AWS::EC2::LaunchTemplate) The launch template for EC2 instances launched by AWS Batch. Used to mount a MATLAB installation to the EC2 instance.
- Security Group (AWS::EC2::SecurityGroup) The security group for EC2 instances launched by AWS Batch.
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IAM Role for container instances (AWS::IAM::Role) Role that allows containers launched by AWS Batch to access Amazon S3 and Amazon Elastic Container Service.
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IAM Instance Profile for container instances (AWS::IAM::InstanceProfile) Profile that associates containers launched by AWS Batch with the IAM Role for container instances.
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IAM Role for AWS Batch (AWS::IAM::Role) Role that provides AWS Batch with the necessary permissions to use other AWS services to run jobs.
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IAM Role for Spot (AWS::IAM::Role) Role that provides AWS Batch with the necessary permissions to run jobs using EC2 Spot.
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IAM Role for Lambda function for multiplication (AWS::IAM::Role) Role that provides permissions to run the Lambda function for multiplication.
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IAM role for deleting S3 bucket contents (AWS::IAM::Role) Role that provides permissions to run the Lambda function to empty S3 bucket.
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Lambda function for multiplication (AWS::Lambda::Function) Lambda function that multiplies two numbers together. Used to calculate the compute environment's maximum number of vCPUs.
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Custom resource for multiplication (Custom::MultiplyFunction) Custom resource that uses the Lambda function for multiplication to calculate the compute environment's maximum number of vCPUs. Multiplies the input parameters "MaxWorkers" and "NumVCPUsPerWorker" together at stack creation.
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Lambda function to empty S3 bucket (AWS::Lambda::Function) Lambda function that empties the S3 bucket at stack deletion. When empty, the S3 bucket can be automatically deleted by Cloud Formation.
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Custom resource to empty S3 bucket (Custom::EmptyBuckets) Custom resource that uses the Lambda function to empty S3 bucket at stack deletion.
Parallel Computing Toolbox and MATLAB Parallel Server software let you solve computationally and data-intensive programs using MATLAB and Simulink on computer clusters, clouds, and grids. Parallel processing constructs such as parallel-for loops and code blocks, distributed arrays, parallel numerical algorithms, and message-passing functions let you implement task-parallel and data-parallel algorithms at a high level in MATLAB. To learn more, see the documentation: Parallel Computing Toolbox and MATLAB Parallel Server.
AWS is a set of cloud services which allow you to build, deploy, and manage applications hosted in Amazon’s global network of data centers. Find out more about the range of cloud-based products offered by AWS. Services deployed in AWS can be created, managed, and deleted using the AWS Management Console. For more information about the AWS Management Console, see AWS Management Console.
Provide suggestions for additional features or capabilities using the following link: MATLAB and Simulink in the Cloud
If you require assistance or have a request for additional features or capabilities, contact MathWorks Technical Support.
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