New purpose-built Amazon EC2 instances for HPC workloads deliver up to 65% better price-performance compared to similar compute-optimized Amazon EC2 instances

Maxar Technologies, DTN, and TotalCAE among customers and partners using Hpc6a instances

Amazon Web Services (AWS), a subsidiary of, Inc. (NASDAQ: AMZN), has announced the general availability of Amazon Elastic Compute Cloud (Amazon EC2) Hpc6a instances, a new instance type designed specifically for closely coupled high-performance computing (HPC) workloads. Hpc6a instances, which are powered by AMD EPYC processors from the third generation, enhance AWS’ HPC compute options and provide up to 65 percent better pricing performance than similar compute-optimized Amazon EC2 instances already used for HPC workloads.

Customers can scale HPC clusters on AWS to run their most compute-intensive workloads like genomics, computational fluid dynamics, weather forecasting, molecular dynamics, computational chemistry, financial risk modeling, computer-aided engineering, and seismic imaging for even less money with Hpc6a instances. Hpc6a instances are available on-demand with no upfront obligations through a low-cost, pay-as-you-go use approach. To get started with Hpc6a instances, visit

HPC is used by organizations in a variety of industries to address their most difficult academic, scientific, and business problems. However, implementing HPC successfully is costly since it necessitates the ability to handle massive volumes of data, which necessitates a big amount of computational power, quick memory and storage, and low-latency networking among HPC clusters. Some companies build their own infrastructure to run HPC workloads, but this requires a large upfront capital investment, lengthy procurement cycles, ongoing overhead management to monitor hardware and keep software current, and limited flexibility when the infrastructure becomes obsolete and must be upgraded.

Customers from a variety of industries choose the cloud to operate their HPC workloads because of the increased security, scalability, and elasticity it provides. Engineers, researchers, and scientists prefer Amazon EC2 instances with advanced networking (e.g. C5n, R5n, M5n, and C6gn) to scale tightly coupled HPC workloads that demand high levels of inter-instance connections with thousands of interdependent tasks. While the performance of these instances is adequate for most HPC use cases, customers are aiming to maximize pricing performance as they run HPC workloads that can scale to tens of thousands of servers on AWS as workloads scale to address increasingly complex issues.

The new Hpc6a instances are designed to provide the best value for money when running HPC applications at scale in the cloud. For HPC workloads requiring complicated calculations, Hpc6a instances provide up to 65 percent higher pricing performance across a range of cluster sizes—up to tens of thousands of cores. Elastic Fabric Adapter (EFA), an Amazon EC2 network interface, is enabled by default on Hpc6a instances. Customers can benefit from low latency, low jitter, and up to 100 Gbps of EFA networking capacity to boost operational efficiency and accelerate time-to-results for workloads that rely on inter-instance interactions using EFA networking. Hpc6a instances are powered by 3rd Gen AMD EPYC processors that run at frequencies up to 3.6 GHz and provide 384 GB of memory. Using Hpc6a instances, customers can more cost-effectively tackle their biggest and most difficult academic, scientific, and business problems with HPC, and realize the benefits of AWS with superior price performance.

“By consistently innovating and creating new purpose-built Amazon EC2 instances for virtually every type of workload, AWS customers have realized huge price performance benefits for some of today’s most business-critical applications. While high performance computing has helped solve some of the most difficult problems in science, engineering, and business, effectively running HPC workloads can be cost-prohibitive for many organizations,” said David Brown, Vice President of Amazon EC2 at AWS. “Purpose-built for HPC workloads, Hpc6a instances now help customers realize up to 65% better price performance for their HPC clusters at virtually any scale, so they can focus on solving the biggest problems that matter to them most without the cost barriers that exist today.”

“We are excited to continue our momentum with AWS and provide their customers with this new, powerful instance for high performance computing workloads,” said Dan McNamara, Senior Vice President and General Manager, Server Business at AMD. “AMD EPYC processors are helping customers of all sizes solve some of their biggest and most complex problems. From small universities to enterprises to large research facilities, Hpc6a instances powered by 3rd Gen AMD EPYC processors open up the world of powerful HPC performance with cloud scalability to more customers around the world.”

Customers can provision Hpc6a instances alongside other instance types using AWS ParallelCluster (an open-source cluster management tool), allowing them the option to run multiple task types optimized for different instances within the same HPC cluster. The AWS Nitro System, a set of building elements that offload many traditional virtualization activities to specialized hardware and software to achieve high performance, high availability, and better security while reducing virtualization overhead, is available for HPC6a instances. On-Demand Instances, Reserved Instances, and Savings Plans are all available for HPC6a instances. HPC6a instances are available in AWS GovCloud (US-West) and US East (Ohio), with availability in more AWS Regions coming soon.

Maxar partners with innovative businesses and more than 50 governments to monitor global change, deliver broadband communications, and advance space operations with capabilities in Space Infrastructure and Earth Intelligence.

“Amazon EC2 Hpc6a instances are yet another exciting announcement from AWS that enables Maxar to continue to meet and exceed our customer requirements for big compute workflows—whether to accelerate the research and operations of Numerical Weather Prediction workloads or to create the world’s best, most up-to-date, and accurate digital twin models with our Maxar Precision3D product suite,” said Dan Nord, SVP and Chief Product Officer at Maxar Technologies

“Hpc6a’s AMD EPYC processors combined with the EFA networking capability provide us a 60% performance improvement over alternatives, while also being more cost efficient. This enables Maxar to strategically choose among the suite of AWS HPC cluster configurations that we’ve developed to best suit our clients’ needs while maximizing flexibility and resiliency.”

DTN’s global weather station network delivers hyper-local, accurate, and real-time weather intelligence to empower organizations with actionable insights.

“Our collaboration with AWS allows us to better serve our customers with high-resolution weather prediction systems that feed analytics engines,” said Lars Ewe, Chief Technology Officer at DTN. “We’re very excited to see the price performance of Hpc6a instances, and we expect this to be our go-to Amazon EC2 instance choice for HPC workloads going forward.”

TotalCAE has over 20 years of experience with HPC for computer-aided engineering (CAE). TotalCAE helps eliminate IT headaches by professionally managing customers’ HPC engineering environment and engineering applications so they can focus on engineering, and not IT.

“TotalCAE Platform makes it easy for CAE departments to adopt the agility and flexibility of AWS in just a few clicks for hundreds of engineering applications like Ansys Fluent, Siemens Simcenter STAR-CCM+, and Dassault Systèmes Abaqus,” said Rod Mach, President at TotalCAE. “As an AWS HPC Competency Partner, we help customers run their CAE workloads in the cloud. With HPC6a instances, we have seen up to a 30% performance boost for computational fluid dynamics workloads at a lower cost, enabling TotalCAE to offer customers industry leading price performance and scalability in the cloud.”

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