Tag: Research Computing

Today we’re announcing Research and Engineering Studio on AWS, a self-service portal to help scientists and engineers access and manage virtual desktops to see their data and run their interactive applications in the cloud.

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 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.

Today we discuss the performance results we saw from the new hpc7a instance, running HPC workloads like CFD, molecular dynamics, and weather prediction codes.

Lawrence Livermore National Laboratory (LLNL) and AWS are again joining forces to provide a training opportunity for emerging HPC tools and application. In this post you’ll find out the details of those tutorials, and find out how to participate.

Today we’re going to show you how you can automate cluster deployment and create self-documenting infrastructure at the same time, which leads to more repeatable results that are easier to manage (and replicate).

Hpc7g is the first Amazon EC2 HPC instance offering with multiple instance sizes, but this is quite different from the experience of getting smaller instances from other non-HPC instance families. Today, we want to take a moment to explore why this is different, and how it helps.

Complicated multi-step workflows can be challenging to deploy, especially when using a variety of high-compute resources. Covalent is an open-source orchestration tool that streamlines the deployment of distributed workloads on AWS resources. In this post, we outline key concepts in Covalent and develop a machine learning workflow for AWS Batch in just a handful of steps.