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AWS ParallelCluster 3.8 with support for Amazon EC2 Capacity Blocks for ML


AWS ParallelCluster 3.8 is now generally available. Key features in this release are support for Rocky Linux 8 and Amazon EC2 Capacity Blocks for ML, allowing you to reserve highly sought-after GPU instances on a future date to support your short duration machine learning (ML) workloads. Other important features in this release include:

  • Scaling strategies to help you meet your scaling and cost requirements, ranging from strict all-or-nothing, that avoid launching idle instances, to best-effort, which prioritizes throughput scaling over avoiding idle instances.
  • Support for mounting user-defined file systems in AWS to the /home directory of the head node, helping you simplify cluster storage management. 
  • Custom Munge key to help you simplify integration of additional cluster resources that require the Scheduler Munge key.

For more details on the release, review the AWS ParallelCluster 3.8 release notes.

AWS ParallelCluster is a fully-supported and maintained open-source cluster management tool that enables R&D customers and their IT administrators to operate high-performance computing (HPC) clusters on AWS. AWS ParallelCluster is designed to automatically and securely provision cloud resources into elastically-scaling HPC clusters capable of running scientific, engineering, and machine-learning (ML/AI) workloads at scale on AWS. 

AWS ParallelCluster is available at no additional charge in the AWS Regions listed here, and you pay only for the AWS resources needed to run your applications. To learn more about launching HPC clusters on AWS, visit the AWS ParallelCluster User Guide. To start using ParallelCluster, see the installation instructions for ParallelCluster UI and CLI.



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