Tag: AWS ParallelCluster

Today we’re announcing the integration between Amazon File Cache and AWS ParallelCluster – super important for hybrid scenarios. We’ll show you how it works and how to deploy it.

In this post, we show how Reezocar uses computer vision to change the way they detect damage and price used vehicles for re-sale in secondary markets. This reduces landfill and helps achieve the goals of the circular economy.

In this post, we discuss the benefits of digital technology for the circular economy, and show how businesses can implement these technologies to get the most out of them for the wellbeing of everyone.

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).

Today, we’ll show you our open-source sample implementation of a web frontend and cloud HPC backend to support researchers using AI tools like AlphaFold for drug discovery and design.

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.

The transition to a sustainable economy is a major goal of many organizations today. HPC plays a pivotal role and in this post we’ll explore how HPC on AWS is enabling the shift towards a sustainable future.

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.