Category: High Performance Computing

Containers are rapidly maturing within the high performance computing (HPC) community and we’re excited to be part of the movement: listening to what customers have to say and feeding this back to both the community and our own product and service teams. Containerization has the potential to unblock HPC environments, so AWS ParallelCluster and container-native schedulers like AWS Batch are moving quickly to reflect the best practices developed by the community and our customers. This year is the seventh consecutive year we are hosting the ‘High Performance Container Workshop’ at ISC High Performance 2021 conference (ISC’21). The workshop will be taking place on July 2nd at 2PM CEST (7AM CST). The full program for the workshop is available on the High Performance Container Workshop page at https://hpcw.github.io/

In this blog post, we will explain how to launch highly available HPC clusters across an AWS Region. The solution is deployed using the AWS Cloud Developer Kit (AWS CDK), a software development framework for defining cloud infrastructure in code and provisioning it through AWS CloudFormation, hiding the complexity of integration between the components.

Today, more than 290,000 researchers in France are working to provide better support and care for patients through modern medical treatment. To fulfill their mission, these researchers must be equipped with powerful tools. At AWS, we believe that technology has a critical role to play in medical research. Why? Because technology can take advantage of the significant amount of data generated in the healthcare system and in the research community to enable opportunities for more accurate diagnoses, and better treatments for many existing and future diseases. To support elite research in France, we are proud to be a sponsor of two French organizations:  Gustave Roussy and Sorbonne University. AWS is providing them with the computing power and machine learning technologies needed to accelerate cancer research and develop a treatment for COVID-19.

Training users on how to use high performance computing resources — and the data that comes out as a result of those analyses — is an essential function of most research organizations. Having a robust, scalable, and easy-to-use platform for on-site and remote training is becoming a requirement for creating a community around your research mission. A great example of this comes from the NOAA National Weather Service Warning Decision Training Division (WDTD), which develops and delivers training on the integrated elements of the hazardous weather warning process within a National Weather Service (NWS) forecast office. In collaboration with the University of Oklahoma’s Cooperative Institute for Mesoscale Meteorological Studies (OU/CIMMS), WDTD conducts its flagship course, the Radar and Applications Course (RAC), for forecasters issuing warnings for flash floods, severe thunderstorms, and tornadoes. Trainees learn the warning process, the science and application of conceptual models, and technical aspects of analyzing radar and other weather data in the Advanced Weather Interactive Processing System (AWIPS). 

Arm and AWS are calling all grad students and post-docs who want to gain experience advancing the adoption of the Arm architecture in HPC to join a world-wide community effort lead by the Arm HPC User’s Group (A-HUG).
The event will take the form of a hackathon this summer and is aimed at getting open-source HPC codes to build and run fast on Arm-based processors, specifically AWS Graviton2.
To make it a bit more exciting, A-HUG will be awarding an Apple M1 MacBook to each member of the team (max. 4 people) that contributes the most back to the Arm HPC community.

The Weather Research and Forecasting (WRF) model is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. With the release of Arm-based AWS Graviton2 Amazon Elastic Compute Cloud (EC2) instances, a common question has been how these instances perform on large-scale NWP workloads. In this blog, we will present results from a standard WRF benchmark simulation and compare across three different instance types.

A customer asked us what is the difference between the CancelJob and TerminateJob API calls in AWS Batch. This post provides an overview of AWS Batch job states, and how these two API calls effect the job requests that you have submitted.

This post was written by Dario La Porta, AWS Professional Services Senior Consultant for HPC. Customers across a wide range of industries such as energy, life sciences, and design and engineering are facing challenges in managing and analyzing their data. Not only is the amount and velocity of data increasing, but so is the complexity and […]

Large-scale data analysis usually involves some multi-step process where the output of one job acts as the input of subsequent jobs. Customers using AWS Batch for data analysis want a simple and performant storage solution to share with and between jobs. We are excited to announce that customers can now use Amazon Elastic File System (Amazon […]

Molecular dynamics (MD) is a simulation method for analyzing the movement and tracing trajectories of atoms and molecules where the dynamics of a system evolve over time. MD simulations are used across various domains such as material sciences, biochemistry, biophysics and are typically used in two broad ways to study a system. The importance of […]