AWS HPC Blog
Category: Compute
Leveraging Seqera Platform on AWS Batch for machine learning workflows – Part 2 of 2
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.
Leveraging Seqera Platform on AWS Batch for machine learning workflows – Part 1 of 2
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.
Save up to 90% using EC2 Spot, even for long-running HPC jobs
New OS-level checkpointing tools can let you run existing HPC codes on EC2 Spot instances with minimal impact from interruptions. Read on for the details.
Enhancing ML workflows with AWS ParallelCluster and Amazon EC2 Capacity Blocks for ML
No more guessing if GPU capacity will be available when you launch ML jobs! EC2 Capacity Blocks for ML let you lock in GPU reservations so you can start tasks on time. Learn how to integrate Caacity Blocks into AWS ParallelCluster to optimize your workflow in our latest technical blog post.
Using a Level 4 Digital Twin for scenario analysis and risk assessment of manufacturing production on AWS
This post was contributed by Orang Vahid (Dir of Engineering Services) and Kayla Rossi (Application Engineer) at Maplesoft, and Ross Pivovar (Solution Architect) and Adam Rasheed (Snr Manager) from Autonomous Computing at AWS One of the most common objectives for our Digital Twin (DT) customers is to use DTs for scenario analysis to assess risk […]
Slurm REST API in AWS ParallelCluster
Looking to integrate AWS ParallelCluster into an automated workflow? This post shows how to submit and monitor jobs programmatically with Slurm REST API (code examples included).
New: Research and Engineering Studio on AWS
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.
Deep-dive into Ansys Fluent performance on Ansys Gateway powered by AWS
In this post, we’ll show you the performance and price curves when Ansys Gateway, powered by AWS runs on different HPC instances – this should help you make the right hardware choices for running Fluent simulations in the cloud.
Lattice Boltzmann simulation with Palabos on AWS using Graviton-based Amazon EC2 Hpc7g instances
In this post we’ll show you the performance when running the Parallel Lattice Boltzmann Solver (Palabos) on the latest generation of AWS Graviton CPUs in Hpc7g instances on AWS.
Using Fleet Training to Improve Level 3 Digital Twin Virtual Sensors with Ansys on AWS
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.