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
Using AWS, Autodesk can scale the use of generative design to run hundreds of simulations in one hour instead of several hours or days. Autodesk develops software for the engineering, design, and entertainment industries.
AWS allowed Cadence to isolate workloads from one another and ensure users and applications didn’t compete for resources. The company was able to run faster, and significantly reduce job times.
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 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.
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.
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.
Oil and Gas
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.
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.
Aon Securities Inc. (ASI) leverages GPU-optimized instances on Amazon EC2 to run its financial simulation platform and lower the calculation and total reporting process time from 10 days to 10 minutes.
Bankinter uses AWS for credit-risk simulation applications that require upto 5,000,000 simulations. Using AWS, Bankinter was able to reduce the average time-to-solution from 23 hours to 20 minutes.
To respond to rapidly changing market dynamics, FINRA moved about 90 percent of its data volumes to Amazon Web Services, using AWS to capture, analyze, and store a daily influx of 37 billion record.
Using AWS, Pacific Life can quickly scale its compute capacity with less cost and IT overhead compared to adding new hardware to its own data centers.
TuSimple built their autonomous driving platform using sophisticated deep learning algorithms developed with Apache MXNet on AWS. TuSimple has used AWS to simulate billions of miles of driving.
AWS provides DriveAI the ability to seamlessly scale as their business grows, and the capability to handle their high performance computing demands.
Universities & Academia (Research Computing)
Learn how UC Santa Cruz Genomics Institute was able to process samples faster and securely get results to collaborators using AWS.
Baylor College of Medicine was able to create a central and secure location for storing hundreds of terabytes of genomic data and complete its own studies 5x faster than with their local infrastructure.
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