This post references AWS ParallelCluster. Check out AWS Parallel Computing Service (AWS PCS), our new managed Slurm service for running HPC and AI workloads on AWS. Introduction The Korean Government announced a national AI initiative to provide high-performance GPU infrastructure for Korea’s national AI research teams. AWS was selected as a supplier of GPU resources […]
This post references AWS ParallelCluster. Check out AWS Parallel Computing Service (AWS PCS), our new managed Slurm service for running HPC and AI workloads on AWS. This post was contributed by Santosh Kumar, Bhagyaraju Kasina, Dr. Sandeep Sovani and Dr. Max Starr Researchers and engineering teams running High Performance Computing (HPC) jobs face a constant […]
This post was contributed by Manu Pillai, Gloria Macia and Natalia Jimenez, PhD Organizations running high-performance computing (HPC) workloads today operate largely as they have for decades: users manually specify required compute specifications for each of their jobs. Users spend valuable time analyzing workload requirements, selecting instance types, and troubleshooting infrastructure issues – time that […]
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 […]