AWS HPC Blog

Category: Compute

Introducing AWS ParallelCluster multiuser support via Active Directory

Today we’re announcing the release of AWS ParallelCluster 3.1 which now supports multiuser authentication based on Active Directory (AD). Starting with v3.1.1 clusters can be configured to use an AD domain managed via one of the AWS Directory Service options like Simple AD or AWS Managed Microsoft AD (MSAD). This blog post describes the new feature, and gives an example of a configuration block for ParallelCluster 3 configuration files.

How to Arm a world-leading forecast model with AWS Graviton and Lambda

The Met Office is the UK’s National Meteorological Service, providing 24×7 world-renowned scientific excellence in weather, climate and environmental forecasts and severe weather warnings for the protection of life and property. They provide forecasts and guidance for the public, to our government and defence colleagues as well as the private sector. As an example, if you’ve been on a plane over Europe, Middle East, or Africa; that plane took off because the Met Office (as one of two World Aviation Forecast Centres) provided a forecast. This article explains one of the ways they use AWS to collect these observations, which has freed them to focus more on top quality delivery for their customers.

Using Spot Instances with AWS ParallelCluster and Amazon FSx for Lustre

Processing large amounts of complex data often requires leveraging a mix of different Amazon EC2 instance types. These types of computations also benefit from shared, high performance, scalable storage like Amazon FSx for Lustre. A way to save costs on your analysis is to use Amazon EC2 Spot Instances, which can help to reduce EC2 costs up to 90% compared to On-Demand Instance pricing. This post will guide you in the creation of a fault-tolerant cluster using AWS ParallelCluster. We will explain how to configure ParallelCluster to automatically unmount the Amazon FSx for Lustre filesystem and resubmit the interrupted jobs back into the queue in the case of Spot interruption events.

Accelerating drug discovery with Amazon EC2 Spot Instances

We have been working with a team of researchers at the Max Planck Institute, helping them adopt the AWS cloud for drug research applications in the pharmaceutical industry. In this post, we’ll focus on how the team at Max Planck obtained thousands of EC2 Spot Instances spread across multiple AWS Regions for running their compute intensive simulations in a cost-effective manner, and how their solution will be enhanced further using the new Spot Placement Score API.

Coming soon: dedicated HPC instances and hybrid functionality

This year, we’ve launched a lot of new capabilities for HPC customers, making AWS the best place for the length and breadth of their workflows. EFA went mainstream and is now available in sixteen instance families for fast fabric capabilities for scaling MPI and NCCL codes. We’ve written deep-dive studies to explore and explain the optimizations that will drive your workloads faster in the cloud than elsewhere. We released a major new version of AWS ParallelCluster with its own API for controlling the cluster lifecycle. AWS Batch became deeply integrated into AWS Step Functions and now supports fair-share scheduling, with multiple levers to control the experience. Today we’re signaling the arrival of a new HPC-dedicated instance family – the Hpc6a – and an enhanced EnginFrame that will bring the best of the cloud and on-premises together in a single interface.

How to manage HPC jobs using a serverless API

HPC systems are traditionally access through a Command Line Interface (CLI) where the users submit and manage their computational jobs. Depending on their experience and sophistication, the CLI can be a daunting experience for users not accustomed in using it. Fortunately, the cloud offers many other options for users to submit and manage their computational jobs. In this blog post we will cover how to create a serverless API to interact with an HPC system in the the cloud built with AWS ParallelCluster.

Figure 1. Architecture of Slurm and user workflows, demonstrating two methods of interacting with Slurm. In the first method, the user accesses the Head Node via SSH and runs helper scripts like sinfo, squeue, sbatch, and scontrol. In the second method, the user issues REST API calls through HTTP to slurmrestd.

Using the Slurm REST API to integrate with distributed architectures on AWS

The Slurm Workload Manager by SchedMD is a popular HPC scheduler and is supported by AWS ParallelCluster, an elastic HPC cluster management service offered by AWS. Traditional HPC workflows involve logging into a head node and running shell commands to submit jobs to a scheduler and check job status. Modern distributed systems often use representational […]

Deep dive into the AWS ParallelCluster 3 configuration file

In September, we announced the release of AWS ParallelCluster 3, a major release with lots of changes and new features. To help get you started migrating your clusters, we provided the Moving from AWS ParallelCluster 2.x to 3.x guide. We know moving versions can be a quite an undertaking, so we’re augmenting that official documentation with additional color and context on a few key areas. With this blog post, we’ll focus on the configuration file format changes for ParallelCluster 3, and how they map back to the same configuration sections for ParallelCluster 2.