Category: Compute

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.

In this post we’ll show you application performance and scaling results from Hpc7g, a new instance powered by AWS Graviton3E across a wide range of HPC workloads and disciplines.

In this post we explore SeatGeek’s load testing system that simulates 50k simultaneous users. Originally built to prep SeatGeek for large-event traffic spikes, it now runs weekly to help them harden their code.

With AWS ParallelCluster 3.6, you can directly specify Slurm settings in the cluster config file – improving reproducibility and another step towards self-documentation for your HPC infrastructure.

In this post, we discuss how Novo Nordisk approached the deployment of a scale-out HPC platform for running AlphaFold, while meeting their enterprise IT requirements and keeping the user experience simple.

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.

AWS ParallelCluster 3.6.0 can now detect GPU failures in HPC and AI/ML tasks. Health checks run at the start of Slurm jobs and if they fail, the job is requeued on another instance. This can increase reliability and prevent wasted spend.

Oxford Nanopore sequencers enables direct, real-time analysis of long DNA or RNA fragments. They work by monitoring changes to an electrical current as nucleic acids are passed through a protein nanopore. The resulting signal is decoded to provide the specific DNA or RNA sequence by virtue of  compute-intensive algorithms called basecallers. This blog post presents the benchmarking results for two of those Oxford Nanopore basecallers — Guppy and Dorado — on AWS. This benchmarking project was conducted in collaboration between G42 Healthcare, Oxford Nanopore Technologies and AWS.

Many applications leverage distributed task systems like Celery to handle asynchronous work. In this post, we describe how to handle compute-intensive Celery tasks using AWS Batch to scale the compute resources and run worker agents.

In this post, we discuss the “tipping point” problem, using HPC at a large scale to simulate the impact of deforestation to the risk of accelerating damage to the Amazon rainforest.