Tag: HPC

This post was contributed by Kambiz Shahim, Ankit Kalyani, and Chris Wright. Oxford Nanopore Technologies used Mountpoint for Amazon S3, AWS Batch, and Nextflow to build EPI2ME Cloud, a managed compute environment for processing human genomes at population-scale reliably and securely while reducing computational costs by 50%. EPI2ME Cloud forms Oxford Nanopore’s suite of local […]

This post was contributed by Ronald Hudson and Nate Haynes High Performance Computing (HPC) on AWS demands precise monitoring, like the racing telemetry used by Formula 1 teams to deliver results. Like race engineers tracking car performance, AWS Parallel Computing Service (AWS PCS) administrators must monitor computing metrics in real-time. This vigilance is critical because […]

This post was contributed by Kirill Bogdanov (Pr. Solutions Architect at AWS) and Alan Parry, (CTO at YellowDog). Large-scale compute grids sit at the heart of modern financial services operations. They power overnight batch runs for regulatory risk and prepare traders for the coming day. During trading, the same grids drive intraday ‘value at risk’ […]

This post was contributed by Stefan Dittforth and Michael Mueller Introduction Oxford Nanopore Technologies (ONT) sequencing enhances genome analysis in research and healthcare with its ability to produce long-read sequencing data in real-time. Long reads improve our ability to detect structural variation, resolve repetitive regions, perform haplotype phasing and analyze full-length transcripts, providing a more […]

Research teams moving from on-premises HPC environments often struggle with the complexity of cloud deployment. Traditional approaches require deep expertise in AWS networking, storage architectures, and Slurm configuration management. A typical manual deployment involves weeks of infrastructure provisioning, network topology design, scheduler configuration, and performance tuning. Research teams with limited platform engineering resources find themselves […]

High performance computing (HPC) workloads continue to grow in scale and complexity. Whether simulating airflow over an aircraft wing, modeling structural behavior under load, or performing crash simulation and multi-physics analysis, these workloads demand sustained compute throughput, high memory bandwidth, and efficient scaling across large clusters. Improvements in any one of these dimensions can reduce […]

In life sciences research, managing large-scale computational resources and data efficiently is important for success. However, traditional on-premises environments often struggle to meet these requirements effectively. This post demonstrates how JSR Corporation transformed their research infrastructure using AWS ParallelCluster and AWS DataSync, achieving a 33% reduction in CPU usage and 85% in storage requirements. JSR’s […]

This post was contributed by Mohamed K. Elshazly, PhD, Kareem Abdol-Hamid, Sam Bydlon, PhD, Aarabhi Achanta, and Mark Azadpour The decarbonization of our modern economy depends on solving a defining scientific challenge: developing batteries that are both safe and high performing. From electrical grids to vehicles and aviation, these energy storage devices must provide power […]

Proteros is a leader in structure-based drug discovery solutions, and supports pharmaceutical, biotechnological, and academic clients with advanced technologies like Cryogenic Electron Microscopy (Cryo-EM) and Protein Crystallography (PX). In this blog post, we’ll explore how Proteros implemented an HPC solution that scales with their scientific ambitions. We’ll talk about how they started with a secure […]

This blog was co-authored by Takehiro Nakajima and Mark Azadpour from AWS and Rintaro Yamada, Rei Kajitani and Ryo Kunimoto from Daiichi Sankyo In recent years, the informatics field of drug discovery has seen a rapid increase in workloads requiring large-scale parallel computing, such as genome analysis, structure prediction, and drug design. Daiichi Sankyo has […]