Category: Compute

Today, we’re diving deep into the open-source frameworks that move MPI messages around, and showing you how work we did in the Open MPI and libfabrics community lead to an improvement for EFA users – and everyone else, too.

AWS Batch recently added support for Graviton and Windows containers on Fargate. Read about how these and other features like large task sizes and configurable local storage make AWS Batch on Fargate a fantastic serverless solution for your batch workloads.

AWS ParallelCluster 3.7 now supports adding login nodes to your cluster, out of the box. Here, we’ll show you how to set this up, and highlight some important tunable options for tweaking the experience.

In this post, we’ll walk you through how banks and other financial services firms migrate or burst their grid workloads onto AWS using AWS ParallelCluster and the Slurm scheduler.

In this post we’ll show how generative AI, combined with conventional physics-based CFD can create a rapid design process to explore new design concepts in automotive and aerospace from just a single image.

In this post we’ll show you how to deploy ParallelCluster in a shared VPC environment so you can separate infrastructure management, cluster operations, and help segregate costs, too.

Today we’re showing you our community library of HPC Recipes for AWS. It’s a public repo @github that will help you achieve feature-rich, reliable HPC deployments ready to run your workloads no matter where you’re starting from.

In this post, we’ll show you an open-source solution for a real-time quant trading system that you can deploy on AWS. We’ll go over the challenges brought on by monitoring portfolios, the solution, and its components. We’ll finish with the installation and configuration process and show you how to use it.

In this post, we hear from Maxar’s WeatherDesk team on how they deploy their HPC workloads using a “fail fast” software development technique so they can be sure of meeting customer deadlines for their business.

In this post, we share how Amazon Search optimizes their use of accelerated compute resources using AWS Batch fair-share scheduling to schedule distributed deep learning workloads.