AWS HPC Blog
Tag: Amazon FSx for Lustre
Second generation EFA: improving HPC and ML application performance in the cloud
Since launch, EFA has seen continuous improvements in performance. In this post, we talk about our 2nd generation of EFA, which takes another step in improving Machine Learning and High Performance Computing in the Cloud.
Expanded filesystems support in AWS ParallelCluster 3.2
AWS ParallelCluster version 3.2 introduces support for two new Amazon FSx filesystem types (NetApp ONTAP and OpenZFS). It also lifts the limit on the number of filesystem mounts you can have on your cluster. We’ll show you how, and help you with the details for getting this going right away.
How Thermo Fisher Scientific Accelerated Cryo-EM using AWS ParallelCluster
In this blog post, we’ll walk you through the process of building a successful Cryo-EM benchmarking pilot using AWS ParallelCluster, Amazon FSx for Lustre, and cryoSPARC (from Structura Biotechnology) and explain some of our design decisions along the way.
Scalable and Cost-Effective Batch Processing for ML workloads with AWS Batch and Amazon FSx
Batch processing is a common need across varied machine learning use cases such as video production, financial modeling, drug discovery, or genomic research. The elasticity of the cloud provides efficient ways to scale and simplify batch processing workloads while cutting costs. In this post, you’ll learn a scalable and cost-effective approach to configure AWS Batch Array jobs to process datasets that are stored on Amazon S3 and presented to compute instances with Amazon FSx for Lustre.