Tag: Scientific Computing

Transforming computer-aided drug design: see how SandboxAQ leverages AWS and generative AI to explore chemical space, more intelligently generating drug candidates.

Learn how to configure email and SMS alerts for job events to stay on top of your HPC workloads with AWS ParallelCluster using Slurm.

AWS Batch multi-node parallel jobs can now run on Amazon EKS to provide gang scheduling of pods across nodes for large scale distributed computing like ML model training. More details here.

Need to cut your carbon footprint without sacrificing productivity? Migrating HPC workloads to the cloud allowed Baker Hughes to reduce emissions by 99%! Get tips for optimizing compute, storage, networking so you can do better.

AWS Batch just grew a neat new feature: Job queue snapshots. This gives you the visibility you need for managing throughput in a dynamic environment – with competing priorities – and across multiple queues and workloads. Today we give you the inside scoop on how this feature works – especially when you’re using fair share scheduling.

Interested in getting hands-on experience with cutting-edge HPC tools? Check out this blog post on an upcoming virtual training series from @LLNL and @AWSCloud. Learn emerging technologies from the experts this August.

Researchers, engineers & scientists – learn how to leverage AWS ParallelCluster with Research & Engineering Studio for a full-featured cloud workspace. Read this post for details on this new integration.

Genomics community: rejoice! Seqera and AWS have teamed up to announce Seqera Containers, an open-source, no cost, reliable way to generate containers.

Aerospace and automotive companies are speeding up their product design using AI. In this post we’ll discuss how they’re using machine learning to shift design cycles from hours to seconds using surrogate models.

We’re excited to share how we’re involved in launching the High Performance Software Foundation to increase access to and adoption of HPC. By bringing together key players to collaborate, we can lower barriers and accelerate development of portable HPC software stacks.