Category: AWS Batch

Run simulations using multiple containers in a single AWS Batch job Matthew Hansen, Principal Solutions Architect, AWS Advanced Computing & Simulation Recently, AWS Batch launched a new feature that makes it possible to run multiple containers within a single job. This enables new scenarios customers have asked about like simulations for autonomous vehicles, multi-robot collaboration, […]

Heads up AWS Batch users! Learn how to get notifications when your job queue gets blocked so you can quickly troubleshoot and keep your workflows moving. Details in our blog.

In this second part of using Nextflow for machine learning for life science workloads, we provide a step-by-step guide, explaining how you can easily deploy a Seqera environment on AWS to run ML and other pipelines.

Nextflow is popular workflow framework for genomics pipelines, but did you know you can also use it for machine-learning? ML is already being used for medical imaging, protein folding, drug discovery, and gene editing. In this post, we explain how to build an example Nextflow pipeline that performs ML model-training and inference for image analysis.

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 is developing new tools that enable easier and faster deployment of level 3/4 digital twins. This post discusses how a fleet calibrated level 3 digital twin can be cost effectively deployed on AWS Cloud.

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.

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