AWS HPC Blog

Today, we’re announcing the availability of Spack configs for AWS ParallelCluster. You can use these configurations to install optimized HPC applications quickly and easily on your AWS-powered HPC clusters.

In this post, AWS Professional Services highlights how they helped data scientists from Amazon Logistics rearchitect their algorithm for improving the efficiency of their supply-chain by making better planning decisions. Leveraging best practices for deploying scalable HPC applications on AWS, the teams saw a 4X improvement in run time.

In this blog, we provide a walkthrough of running Illumina DRAGEN v4.0 genomic analysis pipelines on AWS, showing accuracy and efficiency, copy number analysis, structural variants, SMN callers, repeat expansion detection, and pharmacogenomics insights for complex genes. We also highlight some benchmarking results for runtime, cost, and concordance from the Illumina DRAGEN DNA sequencing pipeline.

As a part of AWS’s “Digital Technologies for a Circular Economy” initiative, we joined forces with Accenture, Intel and Good Chemistry to massively scale quantum chemistry simulations. This is the first and most complex step to discovering new pathways for PFAS destruction for a cleaner world.

In this post, we describe an integration of Open OnDemand with AWS ParallelCluster so admins can provide web-based access to HPC resources beyond what they have at their site, by using the AWS cloud to add new capabilities and extend capacity.

In AWS ParallelCluster 3.4, you can now build HPC clusters that span multiple Amazon EC2 Availability Zones. In this post, we describe how the new feature works, how to use it, and some implications for cluster design that it raises.

Slurm accounting adds flexibility, transparency, and control to operating an #HPC cluster. #AWS #ParallelCluster 3.3.0 can now automatically configure #Slurm accounting whether you are using your own database or Amazon #Aurora.

In this blog post, we benchmark the performance of Sentieon’s DNAseq and DNAscope pipelines using publicly available genomics datasets on AWS. You will gain an understanding of the runtime, cost, and accuracy performance of these germline variant calling pipelines across a wide range of Amazon EC2 instances.

AWS Batch customers often ask for guidance to optimize their architectures and make their workload to scale rapidly. Here we describe an observability solution that provides insights into your AWS Batch architectures and allows you to optimize them for scale and quickly identify potential throughput bottlenecks for jobs and instances.

In this post we recap all the really significant feature released in DCV from 2022 that delighted our customers. Of course, we’re still not done, so expect more in 2023.