AWS provides the most elastic and scalable cloud infrastructure to run your HPC applications. With virtually unlimited capacity, engineers, researchers, and HPC system owners can innovate beyond the limitations of on-premises HPC infrastructure. AWS delivers an integrated suite of services that provides everything needed to quickly and easily build and manage HPC clusters in the cloud to run the most compute intensive workloads across various industry verticals. These workloads span the traditional HPC applications, like genomics, computational chemistry, financial risk modeling, computer aided engineering, weather prediction, and seismic imaging, as well as emerging applications, like machine learning, deep learning, and autonomous driving.
HPC on AWS removes the long wait times and lost productivity often associated with on-premises HPC clusters. Flexible configuration and virtually unlimited scalability allow you to grow and shrink your infrastructure as your workloads dictate, not the other way around. Additionally, with access to a broad portfolio of cloud-based services like Data Analytics, Artificial Intelligence (AI), and Machine Learning (ML), you can redefine traditional HPC workflows to innovate faster.
Today, more cloud-based HPC applications run on AWS than on any other cloud. Customers like Bristol-Myers Squibb, FINRA, BP and Autodesk trust AWS to run their most critical HPC workloads.
By moving your HPC workloads to AWS you can get instant access to the infrastructure capacity you need to run your HPC applications. HPC on AWS eliminates the wait times and long job queues often associated with limited on-premises HPC resources, helping you to get results faster. Additionally, with access to a broad range of cloud-based services, you can innovate faster by combining HPC workflows with new technologies like Artificial Intelligence and Machine Learning.
Moving HPC workloads to the cloud can help increase productivity by matching the infrastructure configuration to the application. With HPC on AWS, engineers are no longer constrained to running their job on the available configuration. Every workload can run on its own on-demand cluster using an optimal set of services for their unique application. Individuals and teams can rapidly scale up or scale down these resources as needed, commissioning or decommissioning HPC clusters in minutes, instead of days or weeks
With HPC on AWS, there are no upfront capital expenditures or lengthy procurement cycles. You pay only for the capacity you use, and our flexible pricing models offer significant cost savings when you process time-flexible, stateless workloads. You can quickly migrate to newer technologies as soon as they are made available on AWS. This removes the risk of on-premises HPC clusters becoming obsolete or poorly utilized as your needs change over time. The result is more efficient HPC spending, and fewer wasted resources
AWS provides the inherent scalability and an ecosystem of partners and tools for running genomics workloads. With HPC on AWS, you can efficiently and dynamically store and compute your data, collaborate with peers, and incorporate analytics and machine learning.
AWS provides the flexibility to support unique CPU and GPU configurations and the scale and elasticity to support spiky optimization workflows, like automated history-matching. This helps engineers iterate and fine-tune models faster and thus accelerate reservoir simulations.
On AWS, MAXAR was able to deliver weather forecast analysis 58% faster than the NOAA weather supercomputer.
Whether you are running thousands of computational fluid dynamics simulations to design sports cars or sequencing the human genome, follow these self-guided workshops to learn how to do it on AWS. Learn how to run popular applications like Simcenter STAR CCM+, GROMACS, Ansys Fluent, Nextflow and more.
Read posts on the AWS HPC Blog Channel to learn about the latest AWS HPC services, best practices for running HPC workloads on AWS, AWS HPC customer stories, and how to integrate your workloads with AWS Partner solutions.
Introducing support for per-job Amazon EFS volumes in AWS Batch
Learn how you can use AWS Batch to create a standard and secure way to provide access to data in Amazon EFS at the individual job level.
Running finite element analysis using Simcenter Nastran on AWS
Learn how you can efficiently perform Simcenter Nastran FEA simulations on Amazon EC2 instances, and take full advantage of the elasticity, scale, advanced technology, and on-demand usage of the AWS Cloud.
Simplify HPC cluster usage with AWS Cloud9 and AWS ParallelCluster
Learn how you can use AWS ParallelCluster with AWS Cloud9 IDE to quickly set up your HPC cluster and enable easy collaboration with their peers and colleagues.
Tune into the HPC Tech Shorts YouTube channel to learn how you to use AWS HPC products and services, and AWS partner solutions to run your largest, most complex HPC workloads in the cloud.
HPC on AWS - Component Services
The services listed below as HPC solution components are a great starting point to set up and manage your HPC cluster. AWS constantly releases new services and features, and we strongly encourage you to explore how adjacent cloud services can help you redefine your HPC workflows.
Security & Compliance
AWS High Performance Computing Competency Partners
AWS High Performance Computing Competency Partners help customers accelerate their digital innovation in the areas of HPC spanning high performance solvers, high throughput computing, HPC workload management, and foundational HPC technology. AWS HPC Competency Partners offer agile, flexible, and cost-effective technology offerings for HPC on AWS supporting genomics, computational chemistry, seismic processing, computer aided engineering, as well as emerging applications, such as deep learning and autonomous driving.