Tag: Storage

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 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 […]

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 […]

Exciting updates to AWS Batch on Amazon EKS! Configurable namespaces, persistent volume claims, and more. Check out our blog post to see how these features can help manage your complex containerized workloads.

Cryo-EM data processing just got a major boost! Learn how AWS Parallel Computing Service can help structural biology teams scale their HPC infrastructure and streamline Cryo-EM research. Discover a recommended reference architecture that leverages the power of the cloud.

Curious about running AI-powered protein folding analyses on AWS? Quantori’s new solution makes it easy to test generative models and visualize results in your own cloud environment.

Discover how AWS Batch’s multi-container features enable large-scale AV/ADAS simulations with the IPG CarMaker simulator. Learn about the challenges of integrating complex, interdependent vehicle systems.

Balyasny Asset Management (BAM), a $22B global investment firm, faced a unique challenge: how to empower 160 investment teams to conduct cutting-edge research across six strategies. Discover how they leveraged AWS Batch and Amazon EKS to supercharge their research capabilities.

Looking to boost storage performance for your #HPC workloads on AWS? Find out how to build a high-speed EC2 cache for under $4/hour that’s fit for purpose in this new blog post.

Running large-scale modeling and simulations just got easier. Check out our new post on integrating AWS Parallel Computing Service with Research and Engineering Studio for individualized access to HPC resources.