Whitepapers, eBooks, and Infographics
High performance computing (HPC) continues to develop at incredible pace, and the convergence of HPC and machine learning—and even quantum computing—is opening up new possibilities. Gain insights faster, and scale up your compute with AWS’ virtually unlimited compute capacity.
The need for faster, larger, more accurate design cycles, along with the performance and cost advantages of GPUs, are all driving the next generation of CFD applications forward. Download this infographic to learn how you can access the latest AWS technologies to accelereate your CFD simulations.
On AWS, researchers can access purpose-built HPC tools and services along with scientific and technical expertise to accelerate the pace of discovery. Learn how AWS customers are able to run workloads like molecular dynamics, medical imaging, modeling and simulations, and genomics with AWS HPC.
As the first cloud-based product to be verified as an Intel Select Solution, AWS ParallelCluster enables customers to easily deploy HPC workloads on AWS. Learn more about how to configure resources with a single parameter or by using pre-built templates.
Read this whitepaper to learn about the purpose-built HPC services and tools you can use to field innovations in healthcare and life sciences. Learn about AWS’s extensive Partner Network and how AWS customers like AstraZeneca and Fred Hutchinson are lowering time-to-results, and running their workloads at scale on AWS.
In this eBook, learn how engineers can leverage the power and speed of high performance computing in the cloud to speed up standard CAE workflows and significantly reduce the cost and time required for each design iteration cycle.
Today, nearly all industries are using computer-aided engineering (CAE) in product development, including: automotive, aerospace, plant engineering, electronics, energy, and consumer goods. In this infographic, learn five reasons why AWS is a great choice to run your CAE workloads.
In this Technology Spotlight, Hyperion Research discusses how the cloud has evolved to support tightly coupled HPC codes.
Learn how you tightly coupled HPC or distributed ML codes can now scale to thousands of cores using Elastic Fabric Adapter, thereby providing you with results faster.
Different EC2 instances are optimized for a range of workloads. Read this paper to learn how you can identify the right EC2 instance to maximize the performance of your HPC application.
This Hyperion Research paper discusses the US Naval Research Laboratory’s use of HPC and cloud capabilities for atmospheric modelling and forecasting. The paper highlights the performance gains and higher scalability obtained with the use of Amazon EC2 C5n instances and Elastic Fabric Adapter.
While adoption of cloud-based HPC solutions is increasing, misconceptions about their cost, security, and performance persist. It’s crucial to challenge these beliefs and break down common barriers to cloud-based HPC to prevent organizations large and small from being held back by outdated, inaccurate information. Learn how AWS can help you get started with HPC in the cloud quickly, securely, and cost-effectively.
Cloud-based HPC solutions are helping to break down barriers to entry for even the smallest teams that need access to high performance computing resources, and many different industries are finding it much easier to get started in HPC as a result.
AWS customers benefit from a data center and network architecture that offers complete flexibility in catering for a variety of HPC workloads. Every use case has its unique needs and this guide helps determine the deal instance and configuration for running your HPC workloads on AWS.
This paper discusses the importance of cloud orchestration in the context of expanding HPC cloud usage and workflow heterogeneity. In this paper Amazon Web Service (AWS) llustrates how sophisticated cloud orchestration can lead to effieient HPC workflows in the cloud.
From weather modeling to genome mapping to the search for extraterrestrial intelligence, HPC is helping to push the boundaries of what’s possible with advanced computing technologies. Once confined to government labs, large enterprises, and select academic organizations, today it is found across a wide range of industries.
Organizations considering investments in high performance computing (HPC) should look deeply at the hidden costs of on-premises solutions. These factors, including lost productivity and missed innovation, can negatively affect other R&D investments that depend on HPC and thus lower revenues.
AWS offers a highly customizable platform and robust partner community, allowing teams to collaborate from anywhere without the need for infrastructure upgrades. Reinvigorate enterprise collaboration previously held back by on-premises infrastructure with HPC on AWS.
High Performance Computing has always been about solving the world's most complex problems. For too long, however, HPC applications and workloads have been constrained by limited on-premises infrastructure capacity, high capital expenditures, and the constant need for technology refreshes.
With access to virtually unlimited infrastructure, researchers are speeding genomic sequencing, reducing the human burdens of clinical trials, and shortening drug discovery timelines. In this infographic, you will see real-world examples of how life sciences researchers are innovating without constraints by moving their HPC workloads to AWS.
In this eBook, you’ll learn how life sciences researchers are speeding time to results and collaborating securely by moving their HPC workloads to AWS. Genomics researchers derive data insights faster using a cloud-based analysis pipeline, and scientists can optimize clinical trials to accelerate the pace of drug discovery while managing expenses carefully.
With HPC on AWS, you can start innovating the way you have always wanted. Whether it is finding oil (seismic processing), producing oil (reservoir simulation), or optimizing production (wellbore, pipeline and facilities simulation), you can stop worrying about the constraints of on-premses HPC infrastucture cost and capacity.
Market volatility, stringent regulations and intense competition are hallmarks of the financial services industry. In this ebook, learn how financial institutions utilize cloud-based software running on high performance computing platforms like HPC on AWS to make better decisions for risk calculations, stress testing, portfolio optimization, predictive modeling, and more.
Semiconductor and electronics companies using electronic design automation (EDA) can significantly accelerate their product development lifecycle and time to market by taking advantage of the near infinite compute , storage, and resources available on AWS. This whitepaper presents an overview of the EDA workflow, recommendations for moving EDA tools to AWS, and the specific AWS architectural components to optimize EDA workloads on AWS.
In this infographic, you’ll see how financial services institutions are solving real-world challenges faster by moving their HPC workloads to AWS. Harnessing the power of Intel® Xeon® processors, these institutions rapidly accelerate credit risk assessments, meet insurance compliance, and detect fraud and market manipulation, while refocusing people and assets toward innovation instead of IT management.
This Hyperion Research technology spotlight examines the dynamics of the fast-evolving Cloud HPC market and why AWS is well positioned to meet the needs of the HPC cloud computing market.
Reference architecture documents
Public data sets
When organizations make data open on AWS, scientists can access and analyze it, delivering innovative solutions to big challenges. AWS makes a variety of Public Data Sets available to researchers and the public, including:
- Landsat 8: All Landsat 8 scenes from 2015 and onward are made available each day, often within hours of production.
- NASA NEX: A collection of Earth science data sets maintained by NASA, including climate change projections and satellite images of the Earth's surface.
- NEXRAD on AWS: Real-time and archival data from the Next Generation Weather Radar (NEXRAD) network.
- 1000 Genomes Project: This dataset contains the full genomic sequence of 1,700 individuals.
- The Cancer Genome Atlas (TCGA): Raw and processed genomic, transcriptomic, and epigenomic data from The Cancer Genome Atlas (TCGA) available to qualified researchers via the Cancer Genomics Cloud.
- The International Cancer Genome Consortium (ICGC): Whole genome sequence data available to qualified researchers via The International Cancer Genome Consortium (ICGC).
See a complete list of Public Datasets available in the AWS Cloud.
AWS Research Initiative
AWS helps researchers process complex workloads by providing the cost-effective, scalable and secure compute, storage, analytics, and artificial intelligence/machine learning capabilities needed to accelerate time-to-science. In addition to cutting edge technology services, AWS provides researchers with access to open data sets, funding resources, and the training critical to stand up their research and accelerate the pace of innovation globally. Learn more >>
Peering with Global Research Networks
By peering with Global Research Networks, AWS gives researchers robust network connections to the AWS cloud. These network connections allow for reliable movement of data between your home institution, distributed data collection sites, and AWS.
AWS Cloud Credits for Research Program
The AWS Cloud Credits for Research Program supports researchers who seek to build cloud-hosted publicly available science-as-a-service applications and tools, perform proof of concept tests in the cloud, or train communities on the usage of the cloud for research workloads.
AWS Global Data Egress Waiver Program
AWS makes cloud budgeting more predictable by waiving data egress fees in the AWS Cloud, for qualified researchers and academic customers. These are fees associated with “data transfer out from AWS to the Internet." Contact your AWS representative to learn more about this program