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Copy file name to clipboardExpand all lines: LICENSE.md
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@@ -4,7 +4,7 @@ The files in this GitHub repository refer to commercial software products and se
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The following license terms apply only to the files in this GitHub repository, including files in this folder and its subfolders, and do not apply to MathWorks Programs. References to “software” and “code” in the following license terms refer to the files in this GitHub repository.
Copy file name to clipboardExpand all lines: README.md
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@@ -57,13 +57,12 @@ You can then deploy this custom image with the MathWorks infrastructure as code
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You can customize the MATLAB release which is installed as part of this custom build.
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This includes MATLAB releases supported by the prebuilt images, as well as earlier MATLAB releases.
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For more details,
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see [Customize MATLAB Parallel Server Release to Install](./packer/v1#customize-matlab-parallel-server-release-to-install).
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see [Customize MATLAB Paralle Server Release to Install](./packer/v1#customize-matlab-parallel-server-release-to-install).
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Platform engineering teams can use these scripts to take advantage of optimizations MathWorks has developed
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for running MathWorks products in the cloud.
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For more details, see [What are the advantages of building images with MathWorks scripts?](#what-are-the-advantages-of-building-images-with-mathworks-scripts)
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# Learn About Cluster Architecture
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This diagram illustrates the cluster architecture created by the template. When you use the [AWS CloudFormation templates](https://aws.amazon.com/cloudformation/) in this repository, it creates the [MATLAB Job Scheduler](#what-is-matlab-job-scheduler) and the following resources. For more information about each resource, see [AWS CloudFormation template reference.](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/template-reference.html)
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Copy file name to clipboardExpand all lines: releases/R2025b/README.md
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|**eu-west-1**|[](https://eu-west-1.console.aws.amazon.com/cloudformation/home?region=eu-west-1#/stacks/create/review?templateURL=https://matlab-parallel-server-aws-win-refarch.s3.amazonaws.com/R2025b/parallel-server-template.json)|
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|**ap-northeast-1**|[](https://ap-northeast-1.console.aws.amazon.com/cloudformation/home?region=ap-northeast-1#/stacks/create/review?templateURL=https://matlab-parallel-server-aws-win-refarch.s3.amazonaws.com/R2025b/parallel-server-template.json)|
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To deploy the cluster in a region not listed above, see [Deploy Cluster in a Custom Region](#deploy-cluster-in-a-custom-region).
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## Step 2. Configure the Cloud Resources
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When autoscaling is disabled, the AWS Auto Scaling group deploys `Number of worker nodes` instances. To change the number of worker nodes, use the AWS Management Console.
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If you enable autoscaling, the [desired capacity](https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-capacity-limits.html) of the AWS Auto Scaling group is regulated by the number of workers needed by the cluster. The number of Amazon EC2 instances is initially set at `Number of worker nodes`. This number fluctuates between the `Minimum` and `Maximum number of worker nodes`. To change these limits after you create the stack, use the AWS Management Console. To change the amount of time idle nodes are preserved, adjust the value of the tag `mwWorkerIdleTimeoutMinutes`.
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If you enable autoscaling, the [desired capacity](https://docs.aws.amazon.com/autoscaling/ec2/userguide/asg-capacity-limits.html) of the AWS Auto Scaling group is regulated by the number of workers needed by the cluster. The number of Amazon EC2 instances is initially set at `Number of worker nodes`. This number fluctuates between the `Minimum` and `Maximum number of worker nodes`. To change these limits after you create the stack, use the AWS Management Console.
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To change the amount of time idle worker nodes are preserved, adjust the value of the tag `mwWorkerIdleTimeoutMinutes` in the Auto Scaling group (default: 10 minutes). See https://docs.aws.amazon.com/autoscaling/ec2/userguide/add-tags.html#add-tags-console to find the steps to modify tags on an Auto Scaling group.
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To disable autoscaling in a deployed stack, redeploy the stack with autoscaling disabled.
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1.**Copy AMI into your account**: Use this AWS quick-create link to copy the latest MATLAB Parallel Server AMI on Windows into your AWS account. Clicking the link opens a CloudFormation template with prepopulated fields. Set the AWS region in the AWS console to your desired region and deploy the template to copy the AMI. Copying takes 5 to 15 minutes. You are responsible for the costs associated with the storage of this AMI and its snapshots in your AWS account. To save costs, delete this AMI and the snapshots if you no longer need it.
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[](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://mathworks-reference-architectures-templates.s3.amazonaws.com/copy-ami-lambda/v1/0/0/copy-ami-lambda.yml&stackName=Copy-of-MATLAB-Parallel-Server-R2025b-AMI¶m_SourceAmiId=ami-094de84b15c357449¶m_SourceRegion=us-east-1¶m_AmiName=Copy%20of%20MATLAB%20Parallel%20Server%20Windows%20R2025b¶m_ReferenceTag=https://github.com/mathworks-ref-arch/matlab-parallel-server-on-aws-win¶m_MWTemplateUrl=https://matlab-parallel-server-aws-win-refarch.s3.amazonaws.com/R2025b/parallel-server-template.json)
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[](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://mathworks-reference-architectures-templates.s3.amazonaws.com/copy-ami-lambda/v1/0/0/copy-ami-lambda.yml&stackName=Copy-of-MATLAB-Parallel-Server--AMI¶m_SourceAmiId=ami-09b1e9cddc1a2241c¶m_SourceRegion=us-east-1¶m_AmiName=Copy%20of%20MATLAB%20Parallel%20Server%20Windows%20¶m_ReferenceTag=https://github.com/mathworks-ref-arch/matlab-parallel-server-on-aws-win¶m_MWTemplateUrl=https://matlab-parallel-server-aws-win-refarch.s3.amazonaws.com/R2025b/parallel-server-template.json)
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2.**Deploy a cluster using your copied AMI**: After your copy is complete and your AMI is ready, use the `LaunchClusterWithCopiedAmi` link in the outputs tab to deploy a cluster in your desired region. You can also share this link or the Custom AMI ID with others in your AWS account to allow them to deploy clusters using the same AMI.
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