AWS HPC Customer Success Stories
Every industry tackles a different set of challenges. AWS HPC solutions help companies from small to large in nearly every industry achieve their HPC objectives with flexible configuration options that simplify operations, save money, and get results to market faster. These workloads span the traditional HPC applications like genomics, life sciences research, financial risk analysis, computer-aided design, and seismic imaging, to the emerging applications like machine learning, deep learning, and autonomous vehicles.
Computer Aided Engineering
Healthcare and Life Sciences
Illumina uses AWS to globally scale its DNA sequencing technologies while driving down costs by 100X and meeting the security requirements of different countries and customers.
Learn how Bristol-Myers Squibb was able to perform intensive clinical trial simulations on AWS with a 98% time savings, which helps them to shorten study time and reduce patient impact.
Learn how Thermo Fisher used AWS to build the Thermo Fisher Cloud, a platform that helps medical researchers and scientists securely store, analyze, and share data globally.
By accessing close to 100,000 CPUs on AWS, the Relay Therapeutics team is able to perform the analysis of billions of compounds in one day, and has lowered their compute costs 50%.
Japanese pharmaceutical company, Shionogi, reduced calculation time by more than 10X for their drug discovery pipeline and has run millions on simulations on AWS HPC.
Learn how DNAnexus built a platform for genomic analysis on AWS to meet the demanding requirements of HIPAA, CAP/CLIA, GxP, and other privacy laws and regulations.
Learn how Celgene enables secure collaboration between its own researchers and academic research labs using AWS.
To rapidly process data at scale, AstraZeneca used Amazon Web Services (AWS) to build a fast, efficient solution for extracting impactful genomics insights.
Fabric Genomics uses AWS to process whole genomes in minutes, help physicians diagnose diseases faster, and scale to support large genomic datasets.
OpenEye Scientific Software uses AWS to save $800,000 yearly, help pharmaceutical companies deploy thousands of processing cores in weeks instead of months, and improve collaboration.
Metabiota’s uses Rescale platform on AWS to manage their pandemic influenza event catalog that requires 18 million simulations and produces 100 TB of uncompressed data.
Using AWS, Igenomix has the on-demand capacity to run highly data-intensive next-generation sequencing (NGS) workloads, so it can analyze 1,150 percent more samples.
Learn how GENALICE processed genomes from 800 Alzheimer’s disease patients in just 60 minutes, which would have taken its competitor more than two weeks to complete.
Using AWS has helped enable Seven Bridges to provide their customers with complex genetics analysis at a large scale and at low cost—typically saving researchers 40% compared to in-house solutions.
By using AWS, Arterys can render multi-dimensional models of the heart across all device types in 10 minutes or less instead of the 90-minute industry standard.
Using AWS, the Smithsonian Institution Data Science Team can scale instances up and down as needed, allowing the team to annotate genomes in parallel while also managing costs.
23andMe migrated to AWS within 4 months. The company ran a compute job on more than 80,000 virtual CPUs increasing efficiency, and completed a 3-week production workload 33% ahead of schedule with optimized costs.
Hess uses AWS to ingest Seismic data at massive scale and improve productivity of their engineers.
With Spiral Suite running on AWS, a problem that once would have required about seven hours of calculation time completes in less than four minutes.
With AWS, Woodside data science teams can deliver a new analytics algorithm in a few weeks, where it would have taken them three to six months previously.
Digital Globe was able to get data to their customers in the shortest amount of time using AWS
By using cutting edge reservoir modeling software from Rock Flow Dynamics on AWS, simulations that would have taken several years to complete was done over a 12-day period.
Storengy has increased its HPC cluster performance by 2.5 times since moving to AWS. With faster performance, Storengy can more quickly validate experiments before moving them into production.
BlocPower decarbonizes buildings while saving millions of dollars by deploying its SaaS BlocMaps using HPC on AWS.
Baker Hughes migrated its computational fluid dynamics applications to AWS, cutting gas turbine design cycle time, saving 40 percent on HPC costs, and reducing its carbon footprint by 99 percent.
Automotive & Autonomous Vehicles
By using AWS, Lyft Level 5 was able to scale their autonmous vehicle (AV) simulations, increase the velocity of their AV developments, and reduce their compute costs by two-thirds.
Universities & Academia (Research Computing)
The HPC facility of the New York University (NYU) Center for Health Informatics and Bioinformatics uses AWS to allow medical informatics and bioinformatics researchers to share data and enable research computing needs that exceed local capacity limits.
San Francisco State University researchers were able to complete research that previously would have taken them weeks in just hours while reducing computing costs by using Amazon EC2 and machine learning techniques
The High Energy Accelerator Research Organization (KEK) in Japan leveraged Amazon Web Services (AWS) to construct a high performance computing (HPC) environment. This HPC environment provides services to analyze data obtained from synchrotron radiation beamlines and cryogenic electron microscopes for universities and private businesses.
The Finnish Meteorological Institute (FMI), an environmental government agency, uses the cloud to distribute open data and operate data services with higher availability and scalability.
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