High Performance Computing (HPC)


High Performance Computing (HPC) allows scientists and engineers to solve complex, compute-intensive problems. HPC applications often require high network performance, fast storage, large amounts of memory, very high compute capabilities, or all of these. AWS enables you to increase the speed of research and reduce time-to-results by running HPC in the cloud and scaling to larger numbers of parallel tasks than would be practical in most on-premises environments. AWS helps to reduce costs by providing CPU, GPU, and FPGA servers on-demand, optimized for specific applications, and without the need for large capital investments.

Benefits of Running HPC on AWS

Enable quick discoveries

Instantly launch or scale up High Performance Computing clusters on AWS. By eliminating job queue times and scaling your cluster as high as needed, when needed, you can reduce the time to market or publication.

Increase productivity

Focus on applications and research output over infrastructure maintenance and upgrades. When AWS upgrades hardware, you can gain access instantaneously — simply rewrite your cluster configuration file and reboot to move to the latest hardware.

Leverage flexible architectures

Let your research dictate infrastructure, not the other way around. With the flexible configuration options AWS provides, you can start with your hypothesis and create HPC clusters that are optimized for your unique application requirements – GPU today, CPU tomorrow.

Enter a rich solutions ecosystem

In addition to core service options for compute, storage, and databases, take advantage of the breadth of services and partners in the AWS ecosystem to enhance your workload. Options range from familiar solutions like NICE and Thinkbox to experimental builds with AWS Lambda.

Facilitate secure collaboration

Collaborate without compromising on security. Every AWS service provides encryption and options to grant granular permissions for each user while maintaining the ability to share data across approved users. Build solutions compliant with HIPAA, FISMA, FedRAMP, PCI, and more.

Pay only for what you use

Let every dollar contribute meaningfully to your mission. Choose from a range of AWS services and only pay for what you use. No more paying for idle compute capacity, no long-term contracts, and no complex licensing involved. Optimize costs further with Amazon EC2 Spot Instances.

Use Cases by Industry


The Algorithms, Machine, and People (AMP) Lab at UC Berkeley leveraged AWS to quickly scale the compute resources needed to analyze the algorithms that are used in genomics work

Computational Chemistry

Novartis built a platform leveraging AWS to run approximately 87,000 compute cores to conduct 39 years of computational chemistry in 9 hours for a cost of $4,232.

Biological Systems Simulation

Penn State moved its research portal to AWS and made it easy for 6,000 researchers worldwide to design more than 50,000 synthetic DNA sequences

Protein Modeling

The Computer Science department at San Francisco State University used Amazon EC2 to reduce costs and turnaround time to run machine learning workloads.

HPC Capabilities on AWS


High Performance Computing workloads on AWS are run on virtual servers, known as instances, enabled by Amazon Elastic Compute Cloud (Amazon EC2). Amazon EC2 provides secure, resizable compute capacity in the cloud and is offered in a wide range of instance types so you can choose one optimized for your workload.


High Performance Computing workload management gains new levels of flexibility in the cloud, making resource and job orchestration an important consideration for your workload. AWS provides a range of solutions for workload orchestration: fully-managed services enable you to focus more on job requests and output over provisioning, configuring and optimizing the cluster and job scheduler, while self-managed solutions enable you to configure and maintain cloud-native clusters yourself, leveraging traditional job schedulers to use on AWS or in hybrid scenarios.


AWS provides several options for storage, ranging from file systems attached to an EC2 instance to high performance object storage. Most HPC applications require shared access to data from multiple EC2 instances via a file system interface. AWS provides a native, scale-out shared file storage service (Amazon EFS) that provides a file system interface and file system semantics. HPC applications can also use AWS’ block storage offerings, either Amazon EBS or EC2 instance store, for general purpose working storage. Amazon S3 and Glacier provides low-cost storage options for long-term storage of large data sets.


The AWS network is designed for scale. Whether your application requires thousands of cores for one tightly-coupled workload, hundreds-of-thousands of cores for embarrassingly-parallel, high-throughput computing (HTC) applications, or a mixture of both, the AWS network offers performance (high bandwidth, low latency) and scalability.

AWS optimizes and custom builds their own hardware specifically for AWS infrastructure. Cut-through routing combined with AWS large scale means even the biggest customers see consistent latency and high bandwidth when using the most challenging application communication patterns. Enhanced networking provides higher I/O performance and lower CPU utilization compared to traditional virtualized network interfaces. This feature provides higher packet per second (PPS) performance, lower inter-instance latencies, and very low network jitter. Enhanced Networking is available in one of two ways and depending on the instance type: Intel 82599 or Amazon ENA.


From preparing simulation input data to interpreting computing job outputs, high performance graphics tasks are part of many HPC workloads. AWS offers several products to improve the performance, cost and flexibility of running OpenGL, Direct/X and other graphics applications. You can accelerate graphics performance by using the GPU-powered G2 and G3 instances or Elastic GPU, and stream Windows graphics with AppStream 2.0, WorkSpaces, or NICE DCV. If you prefer a Linux-based graphics platform, combining the streaming performance of NICE DCV and the EnginFrame HPC portal can deliver end-to-end workflows to end users across on-premises, hybrid cloud, or full-AWS configurations.

Pricing Considerations

The pay-as-you-go approach

AWS offers you a pay-as-you-go approach for pricing for over 70 cloud services. With AWS you pay only for the individual services you need, for as long as you use them, and without requiring long-term contracts or complex licensing. AWS pricing is similar to how you pay for utilities like water or electricity. You only pay for the services you consume, and once you stop using them, there are no additional costs or termination fees.

Compute pricing

There are three main ways to pay for your compute capacity on Amazon EC2: On-Demand, Reserved Instances, and Spot Instances.

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