COVID-19 HPC Consortium

HPC Resources available to fight COVID-19

Please note, as of May 1, 2022, the COVID-19 HPC Consortium is no longer accepting requests for allocations of resources and services to support the pandemic response.  Those with active allocations will still have access to their allocation through the previously stated period. To all those whose research projects have been supported by the Consortium, thank you for your research and impactful results. For those needing access to additional resources, you can either work directly with providers you might already be working with, or pursue allocations through available programs such as through XSEDEINCITE, and other opportunities.

The COVID-19 HPC Consortium encompasses computing capabilities from some of the most powerful and advanced computers in the world. We hope to empower researchers around the world to accelerate understanding of the COVID-19 virus and the development of treatments and vaccines to help address infections. Consortium members manage a range of computing capabilities that span from small clusters to some of the very largest supercomputers in the world.

Preparing your COVID-19 HPC Consortium Request

(Revised 6 May 2022)

NOTE:The 28 October 2020 updates to this page incorporate new guidance reflective of the desire of the Consortium to more actively manage the portfolio of projects accepted by the Consortium.

To request access to resources of the COVID-19 HPC Consortium, you must prepare a description, no longer than three (3) pages, of your proposed work. Do not include any proprietary information in proposals, since your request will be reviewed by staff from a number of consortium sites. 

Review Criteria and Project Expectations

The proposals will be evaluated on the following criteria:

  • Potential near-term benefits for COVID-19 response

  • Feasibility of the technical approach

  • Need for high-performance computing

  • High-performance computing knowledge and experience of the proposing team

  • Estimated computing resource requirements 

The Consortium is particularly, though not exclusively, interested in projects focused on:

  • Understanding and modeling patient response to the virus using large clinical datasets

  • Learning and validating vaccine response models from multiple clinical trials

  • Evaluating combination therapies using repurposed molecules

  • Mutation understanding and mitigation methods

  • Epidemiological models driven by large multi-modal datasets

Please note the following parameters and expectations:

  • Projects supported by the COVID-19 HPC Consortium are intended to provide benefits to COVID-19 response in the near-term (< 6 months). Projects with longer-term benefits will be referred to standard proposal and allocation processes.

  • Allocations of resources are expected to be for a maximum of six (6) months; proposers may submit subsequent proposals for additional resources

  • All supported projects will have the name of the principal investigator, affiliation, project title and project abstract posted to the  COVID-19 HPC Consortium web site.

  • Project PIs are expected to provide brief (~2 paragraphs) updates on a weekly basis.

  • It is expected that teams who receive Consortium access will publish their results in the open scientific literature.  

Further to the last point, the COVID-19 HPC Consortium wishes to catalyze open, pre-competitive results that can impact COVID-19. Because of the strong public component of the Consortium, all project results must be open and publishable.  

If a principal investigator (PI) believes that a project will result in commercializable intellectual property (IP), the PI should work directly with providers that can accommodate commercializable IP requirements.  The information in the Resources section indicates which providers can make such arrangements.

Project Description Outline

To ensure your request is directed to the appropriate resource(s), your description should include the sections outlined here.

A. Scientific/Technical Goal

Describe how your proposed work contributes to our understanding of COVID-19 and improves the nation's ability to respond to the pandemic in the near term (<6 months).

  • What is the scientific/technical goal and pandemic response impact?

  • What is the plan and timetable for getting to the goal?

  • What is the expected period for performance (one week to six months)?

  • Where do you plan to publish your results and in what timeline?

B. Estimate of Compute, Storage and Other Resources

To the extent possible, provide an estimate of the scale and type of the resources needed to complete the work. The information in the Resources section below is available to help you answer this question.  Please be as specific as possible in your resource request along with data supporting the request made.  Also, please indicate your preferred resource(s) as well as alternative resources should there not be sufficient availability of the primary resource(s) you request. 

  • Are there specific computing architectures or systems that are most appropriate (e.g. GPUs, large memory, large core counts on shared memory nodes, etc.)

  • How much computing support will this effort approximately require in terms of core, node, or GPU hours? How does this break down into the number of independent computations and their individual compute requirements?

  • How distributed can the computation be, and can it be split across multiple HPC systems?

  • Can this workload execute in a cloud environment?

  • Describe the storage needs of the project.

  • Does your project require access to any public datasets? If so, please describe these datasets and how you intend to use them.


C. Support Needs

Describe whether collaboration or support from staff at various Consortium Member and Affiliate organizations (e.g. Commercial Cloud Providers. HPC centers, data or tool providers) will be essential, helpful, or unnecessary. Estimates of necessary application support are very helpful. Teams should also identify any restrictions that might apply to the project, such as export-controlled code, ITAR restrictions, proprietary data sets, regional location of compute resources, or personal health information (PHI) or HIPAA restrictions. In such cases, please provide information on security, privacy, and access issues.

D. Team and Team Preparedness

Summarize your team's qualifications and readiness to execute the project both in using the methods proposed and the resources requested.

  • What is the expected lead time before you can begin the simulation runs?

  • What systems have you recently used and how big were the simulation runs?

  • Given that some resources are at federal facilities with restrictions, please provide a list of the team members that will require accounts on resources along with their citizenship.

Document Formatting

While readability is of greatest importance, documents must satisfy the following minimum requirements. Documents that conform to NSF proposal format guidelines will satisfy these guidelines.

  • Margins: Documents must have 2.5-cm (1-inch) margins at the top, bottom, and sides.

  • Fonts and Spacing: The type size used throughout the documents must conform to the following three requirements:
    Use one of the following typefaces identified below:

    • Arial 11, Courier New, or Palatino Linotype at a font size of 10 points or larger;

    • Times New Roman at a font size of 11 points or larger; or

    • Computer Modern family of fonts at a font size of 11 points or larger.

  • A font size of less than 10 points may be used for mathematical formulas or equations, figures, table or diagram captions and when using a Symbol font to insert Greek letters or special characters. PIs are cautioned, however, that the text must still be readable.

  • Type density must be no more than 15 characters per 2.5 cm (1 inch).

  • No more than 6 lines must be within a vertical space of 2.5 cm (1 inch).

* **Page Numbering**: Page numbers should be included in each file by the submitter. Page numbering is not provided by XRAS. * **File Format**: XRAS accepts only PDF file formats.


Submitting your COVID-19 HPC Consortium request 

  1. Create an XSEDE portal account
    • Go to
    • Click on "Sign In" at the upper right, if you have an XSEDE account … 
    • … or click "Create Account" to create one. 
    • To create an account, basic information will be required (name, organization, degree, address, phone, email). 
    • Email verification will be necessary to complete the account creation.
    • Set your username and password.
    • After your account is created, be sure you're logged into
    • IMPORTANT: Each individual should have their own XSEDE account; it is against policy to share user accounts.
  2. Go to the allocation request form
    • Follow this link to go directly to the submission form.
    • Or to navigate to the request form:
      • Click the "Allocations" tab in the XSEDE User Portal,
      • Then select "Submit/Review Request."
      • Select the "COVID-19 HPC Consortium" opportunity.
    • Select "Start a New Submission."
  3. Complete your submission
    • Provide the data required by the form. Fields marked with a red asterisk are required to complete a submission.
    • The most critical screens are the PersonnelTitle/Abstract, and Resources screens.
      • On the Personnel screen, one person must be designated as the Principal Investigator (PI) for the request. Other individuals can be added as co-PIs or Users (but they must have XSEDE accounts).
      • On the Title/Abstract screen, all fields are required.
      • On the Resources screen…
        • Enter "n/a" in the "Disclose Access to Other Compute Resources" field (to allow the form to be submitted).
        • Then, select "COVID-19 HPC Consortium" and enter 1 in the Amount Requested field. 
    • On the Documents screen, select "Add Document" to upload your 3-page document. Select "Main Document" or "Other" as the document Type.
      • Only PDF files can be accepted.
    • You can ignore the Grants and Publications sections. However, you are welcome to enter any supporting agency awards, if applicable.
    • On the Submit screen, select "Submit Request." If necessary, correct any errors and submit the request again.

Resources available for COVID-19 HPC Consortium request 
Click on title to see full description

U.S. Department of Energy (DOE) Advanced Scientific Computing Research (ASCR)
Supercomputing facilities at DOE offer some of the most powerful resources for scientific computing in the world. The Argonne Leadership Computing Facility (ALCF) and Oak Ridge Leadership Computing Facility (OLCF) and the Lawrence Berkeley National Laboratory (LBNL) may be used for modeling and simulation coupled with machine and deep learning techniques to study a range of areas, including examining underlying protein structure, classifying the evolution of the virus, understanding mutation, uncovering important differences, and similarities with the 2002-2003 SARS virus, searching for potential vaccine and antiviral, compounds, and simulating the spread of COVID-19 and the effectiveness of countermeasure options.


Oak Ridge Summit | 200 PF, 4608 nodes, IBM POWER9/NVIDIA Volta

Summit System

 2 x IBM POWER9 per node
42 TF per node
6 x NVIDIA Volta GPUs per node
512 GB DDR4 + 96 GB HBM2 (GPU memory) per node
1600 GB per node
2 x Mellanox EDR IB adapters (100 Gbps per adapter)
250 PB, 2.5 TB/s, IBM Spectrum Scale storage


Argonne Theta | 11.69 PF, 4292 nodes, Intel Knights Landing

1 x Intel KNL 7230 per node, 64 cores per CPU
192 GB DDR4, 16 GB MCDRAM memory per node
128 GB local storage per node
Aries dragonfly network
10 PB Lustre + 1 PB IBM Spectrum Scale storage
Full details available at:


Lawrence Berkeley National Laboratory 

LBNL Cori | 32 PF, 12,056 Intel Xeon Phi and Xeon nodes
9,668 nodes, each with one 68-core Intel Xeon Phi Processor 7250 (KNL)
96 GB DDR4 and 16 GB MCDRAM memory per KNL node
2,388 nodes, each with two 16-core Intel Xeon Processor E5-2698 v3 (Haswell)
128 GB DDR4 memory per Haswell node
Cray Aries dragonfly high speed network
30 PB Lustre file system and 1.8 PB Cray DataWarp flash storage
Full details at:

U.S. DOE National Nuclear Security Administration (NNSA)

Established by Congress in 2000, NNSA is a semi-autonomous agency within the U.S. Department of Energy responsible for enhancing national security through the military application of nuclear science. NNSA resources at Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), and Sandia National Laboratories (SNL) are being made available to the COVID-19 HPC Consortium.

Lawrence Livermore + Los Alamos + Sandia | 32.2 PF, 7375 nodes, IBM POWER8/9, Intel Xeon
  • LLNL Lassen
    • 23 PFLOPS, 788 compute nodes, IBM Power9/NVIDIA Volta GV100
    • 28 TF per node
    • 2 x IBM POWER9 CPUs (44 cores) per node
    • 4 x NVIDIA Volta GPUs per node
    • 256 BD DDR4 + 64 GB HBM2 (GPU memory) per node
    • 1600 GB NVMe local storage per node
    • 2 x Mellanox EDR IB (100Gb/s per adapter)
    • 24 PB storage
  • LLNL Quartz
    • 3.2 PF, 3004 compute nodes, Intel Broadwell
    • 1.2 TF per node
    • 2 x Intel Xeon E5-2695 CPUs (36 cores) per node
    • 128 GB memory per node
    • 1 x Intel Omni-Path IB (100Gb/s)
    • 30 PB storage (shared with other clusters)
  • LLNL Pascal
    • 0.9 PF, 163 compute nodes, Intel Broadwell CPUs/NVIDIA Pascal P100
    • 11.6 TF per node
    • 2 x Intel Xeon E5-2695 CPUs (36 cores) per node
    • 2 x NVIDIA Pascal P100 GPUs per node
    • 256 GB memory + 32 HBM2 (GPU memory) per node
    • 1 x Mellanox EDR IB (100Gb/s)
    • 30 PB storage (shared with other clusters) 
  • LLNL Ray
    • 1.0   PF, 54 compute nodes, IBM Power8/NVIDIA Pascal P100
    • 19 TF per node
    • 2 x IBM Power8 CPUs (20 cores) per node
    • 4 x NVIDIA Pascal P100 GPUs per node
    • 256 GB + 64 GB HBM2 (GPU memory) per node
    • 1600 GB NVMe local storage per node
    • 2 x Mellanox EDR IB (100Gb/s per adapter)
    • 1.5 PB storage
  • LLNL Surface
    • 506 TF, 158 compute nodes, Intel Sandy Bridge/NVIDIA Kepler K40m
    • 3.2 TF per node
    • 2 x Intel Xeon E5-2670 CPUs (16 cores) per node
    • 3 x NVIDIA Kepler K40m GPUs
    • 256 GB memory + 36 GB GDDR5 (GPU memory) per node
    • 1 x Mellanox FDR IB (56Gb/s)
    • 30 PB storage (shared with other clusters)
  • LLNL Syrah
    • 108 TF, 316 compute nodes, Intel Sandy Bridge
    • 0.3 TF per node
    • 2 x Intel Xeon E5-2670 CPUs (16 cores) per node
    • 64 GB memory per node
    • 1 x QLogic IB (40Gb/s)
    • 30 PB storage (shared with other clusters)
  • LANL Snow
    • 445 TF, 368 compute nodes, Intel Broadwell
    • 1.2 TF per node
    • 2 x Intel Xeon E5-2695 CPUs (36 cores) per node
    • 128 GB memory per node
    • 1 x Intel Omni-Path IB (100Gb/s)
    • 15.2 PB storage
  • LANL Badger
    • 790 TF, 660 compute nodes, Intel Broadwell
    • 1.2 TF per node
    • 2 x Intel Xeon E5-2695 CPUs (36 cores) per node
    • 128 GB memory per node
    • 1 x Intel Omni-Path IB (100Gb/s)
    • 15.2 PB storage
U.S. DOE Office of Nuclear Energy

Idaho National Laboratory | 6 PF, 2079 nodes, Intel Xeon

  • Sawtooth |6 PF; 2079 compute nodes; 99,792 cores; 108 NVIDIA Tesla V100 GPUs
    • Mellanox Infiniband EDR, hypercube
    • CPU-only nodes:
      • 2052 nodes, 2 x Intel Xeon 8268 CPUs
      • 192 GB Ram/node
    • CPU/GPU nodes:
      • 27 nodes, 2 x Intel Xeon 8268 CPUs
      • 384 GB Ram/node
      • 4 NVIDIA Tesla V100 GPUs
Rensselaer Polytechnic Institute
The Rensselaer Polytechnic Institute (RPI) Center for Computational Innovations is solving problems for next-generation research through the use of massively parallel computation and data analytics. The center supports researchers, faculty, and students a diverse spectrum of disciplines. RPI is making its Artificial Intelligence Multiprocessing Optimized System (AiMOS) system available to the COVID-19 HPC Consortium. AiMOS is an 8-petaflop IBM Power9/Volta supercomputer configured to enable users to explore new AI applications.


RPI AiMOS | 11.1 PF, 252 nodes POWER9/Volta

2 x IBM POWER9 CPU per node, 20 cores per CPU
6 x NVIDIA Tesla GV100 per node
32 GB HBM per GPU
512 GB DRAM per node
1.6 TB NVMe per node
Mellanox EDR InfiniBand
11 PB IBM Spectrum Scale storage

MIT/Massachusetts Green HPC Center (MGHPCC)
MIT is contributing two HPC systems to the COVID-19 HPC Consortium. The MIT Supercloud, a 7-petaflops Intel x86/NVIDIA Volta HPC cluster, is designed to support research projects that require significant compute, memory or big data resources. Satori, is a 2-petaflops scalable AI-oriented hardware resource for research computing at MIT composed of 64 IBM Power9/Volta nodes. The MIT resources are installed at the Massachusetts Green HPC Center (MGHPCC), which operates as a joint venture between Boston University, Harvard University, MIT, Northeastern University, and the University of Massachusetts.


MIT/MGHPCC Supercloud | 6.9 PF, 440 nodes Intel Xeon/Volta

2 x Intel Xeon (18 CPU cores per node)
2 x NVIDIA V100 GPUs pe node
32 GB HBM per GPU
Mellanox EDR InfiniBand
3 PB scratch storage

MIT/MGHPCC Satori | 2.0 PF, 64 nodes IBM POWER9/NVIDIA Volta

2 x POWER9 , 40  cores per node
4 x NVIDIA Volta GPUs per node (256 total)
32 GB HBM per GPU
1.6 TB NVMe per node
Mellanox EDR InfiniBand
2 PB scratch storage



IBM Cloud

bx2-16x64 with 16 vCPUs, 64GB RAM and 32 Gbps
bx2-48x192 with 48 vCPUs, 192 GB RAM and 80 Gbps

cx2-16x32 with 16 vCPUs, 32 GB RAM and 32 Gbps
cx2-32x64 with 32 vCPUs, 64 GB RAM and 64 Gbps

mx2-16x128 with 16 vCPUs, 128 GB RAM and 32 Gbps
mx2-32x256 with 32 vCPUs, 256 GB RAM and 64 Gbps

Cloud Object Storage

Job Scheduling:
IBM Spectrum LSF managed instances for easy job submission and monitoring.

IBM Research

IBM Research is providing our WSC 2.8 PF, 54 node, IBM POWER9/NVIDIA Volta high performance computing cluster as well as software tools to help accelerate discovery.

2 x POWER9 CPU per node, 22 cores per CPU
6 x NVIDIA Volta GPUs per node (336 total)
512 GiB DRAM per node
1.4 TB NVMe per node
2 x Mellanox EDR InfiniBand
2 PB IBM Spectrum Scale storage

Deep Search: The Deep Search platform for COVID-19 helps researchers to quickly find and aggregate information in the exponentially growing literature related to COVID-19. Examples of such information are the list of all reported used drugs so far.
Drug Candidate Exploration: To help researchers generate potential new drug candidates for COVID-19, we have applied our novel AI generative frameworks to three COVID-19 targets and have generated 3000 novel molecules. We are sharing these molecules under a Creative Commons license.
Functional Genomics Platform: IBM Functional Genomics Platform is a cloud-based data repository that accelerates the study of microbial life at scale with specifically curated molecular sequence data to fight COVID-19.

U.S. National Science Foundation (NSF)

The NSF Office of Advanced Cyberinfrastructure supports and coordinates the development, acquisition, and provision of state-of-the-art cyberinfrastructure resources, tools and services essential to the advancement and transformation of science and engineering. By fostering a vibrant ecosystem of technologies and a skilled workforce of developers, researchers, staff and users, OAC serves the growing community of scientists and engineers, across all disciplines. The most capable resources supported by NSF OAC are being made available to support the COVID-19 HPC Consortium.

Frontera | 38.7 PF, 8114 nodes, Intel Xeon, NVIDIA RTX GPU

Funded by the National Science Foundation and Operated by the Texas Advanced Computing Center (TACC), Frontera provides a balanced set of capabilities that supports both capability and capacity simulation, data-intensive science, visualization, and data analysis, as well as emerging applications in AI and deep learning. Frontera has two computing subsystems, a primary computing system focused on double precision performance, and a second subsystem focused on single-precision streaming-memory computing.  Frontera is built by Dell, Intel, DataDirect Networks, Mellanox, NVIDIA, and GRC.

Expanse | 5.63 PF, total 844 nodes, AMD EPYC 7742 (Rome), NVIDIA Volta (V100) GPUs

Operated by the San Diego Supercomputer Center (SDSC), Expanse is a cluster designed by Dell and SDSC delivering 5.63 peak petaflops. Expanse's 784 standard compute nodes are each powered by two 64-core AMD EPYC 7742 processors and contain 256 GB of DDR4 memory. The cluster also has 56 GPU nodes each containing four NVIDIA V100s (32 GB SMX2) connected via NVLINK and dual 20-core Intel Xeon 6248 CPUs. Expanse also has four 2 TB large memory nodes.

Stampede2 | 19.3 PF, 4200 Intel KNL, 1,736 Intel Xeon

Operated by TACC, Stampede 2 is a nearly 20-petaflop HPC national resource accessible to  thousands of researchers across the country, including to enable new computational and data-driven scientific and engineering, research and educational discoveries and advances. 

Longhorn | 2.8 PF, 112 nodes, IBM POWER9, NVIDIA Volta

Longhorn is a TACC resource built in partnership with IBM to support GPU-accelerated workloads. The power of this system is in its multiple GPUs per node, and it is intended to support sophisticated workloads that require high GPU density and little CPU compute. Longhorn will support double-precision machine learning and deep learning workloads that can be accelerated by GPU-powered frameworks, as well as general purpose GPU calculations.

Bridges-2 | 5.1 PF, 542 nodes, AMD EPYC 7742 (Rome), NVIDIA Volta (V100) GPUs [NEED UPDATE]

Operated by the Pittsburgh Supercomputing Center (PSC), Bridges-2 provides a heterogeneous research computing platform focused on supporting rapidly-evolving and data-centric computing. Bridges-2 was built in collaboration with Hewlett-Packard Enterprise (HPE) and contains 504 regular compute nodes each powered by 2 64-core AMD EPYC 7742 processors and contain 256 GB of DDR4 memory (with 16 containing 512 GB for larger memory applications), 4 extreme memory nodes each with 4 TB of DDR4 memory, and 24 GPU nodes each containing 8 NVIDIA V100s (32GB SMX2) connected via NVLink (there are 9 additional nodes that contain 8 NVIDIA V100s (16 GB SMX2) and an NVIDIA DGX-2 as well).

Jetstream | 320 nodes, Cloud accessible

Operated by a team led by the Indiana University Pervasive Technology Institute, Jetstream is a configurable large-scale computing resource that leverages both on-demand and persistent virtual machine technology to support a wide array of software environments and services through incorporating elements of commercial cloud computing resources with some of the best software in existence for solving important scientific problems.  

OSG | Distributed High Throughput Computing, 10,000+ nodes, Intel x86-compatible CPUs, various NVIDIA GPUs

The OSG (formerly "Open Science Grid") is a large virtual cluster of distributed high-throughput computing (dHTC) capacity shared by numerous national labs, universities, and non-profits, with the ability to seamlessly integrate cloud resources, too. The OSG Connect service makes this large distributed system available to researchers, who can individually use up to tens of thousands of CPU cores and up to hundreds of GPUs, along with significant support from the OSG team. Ideal work includes parameter optimization/sweeps, molecular docking, image processing, many bioinformatics tasks, and other work that can run as numerous independent tasks each needing 1-8 CPU cores, <20 GB RAM, and <10GB input or output data, though these can be exceeded significantly by integrating cloud resources and other clusters, including many of those contributing to the COVID-19 HPC Consortium.

Anvil | 5.3 PF, 1000 nodes of AMD EPYC 7763 CPUs, 64 NVIDIA A100 Tensor Core GPUs, 32 large memory AMD EPYC 7763 nodes
Operated by Purdue University Research Computing (RCAC), Anvil is a cluster developed in a partnership with Dell delivering 5.3 peak petaflops of capacity. Anvil's 1000 standard compute nodes are each powered by two 64-core 3rd generation AMD EPYC processors and contain 256 GB of DDR4-3200 memory and 240GB local disk. The cluster also has 16 GPU nodes each containing four NVIDIA A100 GPUs connected via NVLINK and two AMD EPYC 7763 CPUs providing an additional 1.5 PF of single-precision performance. In addition, Anvil offers 32 AMD EPYC 7763 CPU large memory nodes, each providing 1 TB of memory.
NASA High-End Computing Capability

NASA Supercomputing Systems | 19.13 PF, 15800 nodes Intel x86

NASA's High-End Computing Capability (HECC) Portfolio provides world-class high-end computing, storage, and associated services to enable NASA-sponsored scientists and engineers supporting NASA programs to broadly and productively employ large-scale modeling, simulation, and analysis to achieve successful mission outcomes.

NASA's Ames Research Center in Silicon Valley hosts the agency's most powerful supercomputing facilities. To help meet the COVID-19 challenge facing the nation and the world, HECC is offering access to NASA's high-performance computing (HPC) resources for researchers requiring HPC to support their efforts to combat this virus. 


NASA Supercomputing Systems | 19.39 PF, 17609 nodes Intel Xeon

AITKEN | 3.69 PF, 1,152 nodes, Intel Xeon
ELECTRA | 8.32 PF, 3,456 nodes, Intel Xeon
PLEIDES | 7.09 PF, 11,207 nodes, Intel Xeon, NVIDIA K40, Volta GPUs
ENDEAVOR | 32 TF, 2 nodes, Intel Xeon
MEROPE | 253 TF, 1792 nodes, Intel Xeon

Amazon Web Services
As part of the COVID-19 HPC Consortium, AWS is offering research institutions and companies technical support and promotional credits for the use of AWS services to advance research on diagnosis, treatment, and vaccine studies to accelerate our collective understanding of the novel coronavirus (COVID-19). Researchers and scientists working on time-critical projects can use AWS to instantly access virtually unlimited infrastructure capacity, and the latest technologies in compute, storage and networking to accelerate time to results. Learn more here.
Microsoft Azure High Performance Computing (HPC)

Microsoft Azure offers purpose-built compute and storage specifically designed to handle the most demanding computationally and data intensive scientific workflows. Azure is optimized for applications such as genomics, precision medicine and clinical trials in life sciences.  

Our team of HPC experts and AI for Health data science experts, whose mission is to improve the health of people and communities worldwide, are available to collaborate with COVID-19 researchers as they tackle this critical challenge. More broadly, Microsoft's research scientists across the world, spanning computer science, biology, medicine, and public health, will be available to provide advice and collaborate per mutual interest.

Azure HPC helps improve the efficiency of drug development process with power and scale for computationally intensive stochastic modeling and simulation workloads, such as population pharmacokinetic and pharmacokinetic-pharmacodynamic modeling.

Microsoft will give access to our Azure cloud and HPC capabilities.

HPC-optimized and AI Optimized virtual machines (VM)

·        Memory BW Intensive CPUs: Azure HBv2 Instances (AMD EPYC™ 7002-series | 4GB RAM per core | 200Gb/s HDR InfiniBand)

·        Compute Intensive CPUs: Azure HC Instances (Intel Xeon Platinum 8168 | 8GB RAM per core | 100Gb/s EDR InfiniBand)

·        GPU Intensive RDMA connected: Azure NDv2 Instances (8 NVIDIA V100 Tensor Core GPUs with NVIDIA NVLink interconnected GPUs | 32GB RAM each | 40 non-hyperthreaded Intel Xeon Platinum 8168 processor cores | 100Gb/s EDR InfiniBand)

·        See the full list of HPC-optimized VM's (H-SeriesNC-Series, and ND-Series)


Storage Options:

·        Azure HPC Cache | Azure NetApp Files | Azure Blog Storage | Cray ClusterStor



·        Azure CycleCloud


Batch scheduler


Azure HPC life sciences:

Azure HPC web site:
AI for Health web site:

Hewlett Packard Enterprise
As part of this new effort to attack the novel coronavirus (COVID-19) pandemic, Hewlett Packard Enterprise is committing to providing supercomputing software and applications expertise free of charge to help researchers port, run, and optimize essential applications. Our HPE Artificial Intelligence (AI) experts are collaborating to support the COVID-19 Open Research Dataset and several other COVID-19 initiatives for which AI can drive critical breakthroughs. They will develop AI tools to mine data across thousands of scholarly articles related to COVID-19 and related coronaviruses to help the medical community develop answers to high-priority scientific questions. We encourage researchers to submit any COVID-19 related proposals to the consortium's online portal. More information can be found here:

Transform research data into valuable insights and conduct large-scale analyses with the power of Google Cloud. As part of the COVID-19 HPC Consortium, Google is providing access to Google Cloud HPC resources for academic researchers.



A task force of NVIDIA researchers and data scientists with expertise in AI and HPC will help optimize research projects on the Consortium's supercomputers. The NVIDIA team has expertise across a variety of domains, including AI, supercomputing, drug discovery, molecular dynamics, genomics, medical imaging and data analytics. NVIDIA will also contribute the packaging of software for relevant AI and life-sciences software applications through NVIDIA NGC, a hub for GPU-accelerated software. The company is also providing compute time on an AI supercomputer, SaturnV.


D. E. Shaw Research Anton 2 at PSC

Operated by the Pittsburgh Supercomputing Center (PSC) with support from National Institutes of Health award R01GM116961, Anton 2 is a special-purpose supercomputer for molecular dynamics (MD) simulations developed and provided without cost by D. E. Shaw Research. For more information, see


Intel will provide HPC /AI and HLS subject matter experts and engineers to collaborate on COVID-19 code enhancements to benefit the community. Intel will also provide licenses for High Performance Computing software development tools for the research programs selected by the COVID-19 HPC Consortium. The integrated tool suites include Intel's C++ and Fortran Compilers, performance libraries, and performance-analysis tools.

Ohio Supercomputer Center

The Ohio Supercomputer Center (OSC), a member of the Ohio Technology Consortium of the Ohio Department of Higher Education, addresses the rising computational demands of academic and industrial research communities by providing a robust shared infrastructure and proven expertise in advanced modeling, simulation and analysis. OSC empowers scientists with the vital resources essential to make extraordinary discoveries and innovations, partners with businesses and industry to leverage computational science as a competitive force in the global knowledge economy, and leads efforts to equip the workforce with the key technology skills required to secure 21st century jobs. For more, visit

  • OSC Owens | 1.6 PF, 824 nodes Intel Xeon/Pascal
    • 2 x Intel Xeon (28 cores per node, 48 cores per big-mem node)
    • 160 NIVIDIA P100 GPUs (1 per node)
    • 128 GB per node (1.5TB per big-mem node)
    • Mellanox EDR Infiniband
    • 12.5 PB Project and Scratch storage
  • OSC Pitzer | 1.3.PF, 260 nodes Intel Xeon/Volta
    • 2 x Intel Xeon (40 cores per node, 80 cores per big-mem node)
    • 64 NIVIDIA V100 GPUs (2 per node)
    • 192 GB per node (384 GB per GPU node, 3TB per big-mem node)
    • Mellanox EDR Infiniband
    • 12.5 PB Project and Scratch storage


The Zenith cluster is the result of a partnership between Dell and Intel®. On the TOP500 list of fastest supercomputers in the world, Zenith includes Intel Xeon® Scalable Processors, Omni‑Path fabric architecture, data center storage solutions, FPGAs, adapters, software and tools. Projects underway include image classification to identify disease in X-rays, MRI scan matching to thoughts and actions, and building faster neural networks to drive recommendation engines. Zenith is available to researchers via the COVD-19 HPC Consortium via standard the application process, subject to availability.

Zenith Configuration:

  • Servers:
    • 422 PowerEdge C6420 servers  
    • 160x PowerEdge C6320p servers
    • 4 PowerEdge R740 servers with Intel – FPGAs
  • Processors
    • 2nd generation Intel Xeon Scalable processors
    • Intel Xeon Phi™
  • • Memory
    • 192GB at 2,933MHz per node (Xeon Gold)
    • 96GB at 2,400MHz per node (Xeon Phi)
  • Operating System: Red Hat® Enterprise Linux® 7
  • Host channel adapter (HCA) card: Intel Omni‑Path Host Fabric Interface Storage
  • Storage
    • 2.68PB Ready Architecture for HPC Lustre Storage
    • 480TB Ready Solutions for HPC NFS Storage
    • 174TB Isilon F800 all-flash NAS storage
UK Digital Research Infrastructure
The UK Digital Research Infrastructure consists of a range of advanced computing systems from academic and UK government agencies with a wide range of different capabilities and capacities. Expertise in porting, developing and testing software is also available from the research software engineers (RSEs) supporting the systems.

Specific technical details on the systems available:

  • ARCHER | 4920 nodes (118,080 cores), two 2.7 GHz, 12-core Intel Xeon E5-2697 v2 per node. 4544 nodes with 64 GB memory nodes and 376 with 128 GB. Cray Aries interconnect. 4.4 PB high-performance storage.
  • Cirrus | 280 nodes (10080 cores), two 2.1GHz 18 core Intel Xeon E5-2695 per node. 256 GB memory per node; 2 GPU nodes each containing two 2.4 Ghz, 20 core Intel Xeon 6148 processors and four NVIDIA Tesla V100-PCIE-16GB GPU accelerators. Mellanox FDR interconnect. 144 NVIDIA V100 GPUs in 36 Plainfield blades (2 Intel Cascade Lake processors and 4 GPUs per node).
  • DiRAC Data Intensive Service (Cambridge) | 484 nodes (15488 cores), two Intel Xeon 6142 per node, 192 GB or 384 GB memory per node; 11 nodes with 4x Nvidia P100 GPUs and 96 GB memory per node; 342 nodes of Intel Xeon Phi with 96 GB memory per node.
  • DiRAC Data Intensive Service (Leicester) | 408 nodes (14688 cores), two Intel Xeon 6140 per node, 192 GB memory per node; 1x 6 TB RAM server with 144 Intel Xeon 6154 cores; 3x 1.5TB RAM servers with 36 Intel Xeon 6140 cores;  64 nodes (4096 cores) Arm ThunderX2 with 128 GB RAM/node.
  • DiRAC Extreme Scaling Service (Edinburgh) | 1468 nodes (35,232 cores), two Intel Xeon 4116 per node, 96 GB RAM/node. Dual rail Intel OPA interconnect.
  • DiRAC Memory Intensive Service (Durham) | 452 nodes (12,656 cores), two Intel Xeon 5120 per node, 512 GB RAM/node, 440TB flash volume for checkpointing.
  • Isambard | 332 nodes (21,248 cores), two Arm-based Marvell ThunderX2 32 core 2.1 GHz per node. 256 GB memory per node. Cray Aries interconnect. 75 TB high-performance storage.
  • JADE | 22x Nvidia DGX-1V nodes with 8x Nvidia V100 16GB and 2x 20 core Intel Xeon E5-2698 per node.
  • MMM Hub (Thomas) | 700 nodes (17000 cores), 2x 12 core Intel Xeon E5-2650v4 2.1 GHz per node, 128 GB RAM/node.
  • NI-HPC | 60x Dell PowerEdge R6525, two AMD Rome 64-core 7702 per node. 768GB RAM/node; 4x Dell PowerEdge R6525 with 2TB RAM; 8 x Dell DSS8440 (each with 2x Intel Xeon 8168 24-core). Provides 32x Nvidia Tesla V100 32GB.
  • XCK | 96 nodes (6144 cores), one 1.3 GHz, 64-core Intel Xeon Phi 7320 per node + 20 nodes (640 cores), two 2.3 Ghz, 16 core Intel Xeon E5-2698 v3 per node. 16 GB fast memory + 96 GB DDR per Xeon Phi node, 128 GB per Xeon node. Cray Aries interconnect. 9TB of DataWarp storage and 650 TB of high-performance storage.
  • XCS | 6720 nodes (241,920 cores), two Intel Xeon 2.1 GHz, 18-core E5-2695 v4 series per node. All with 128 GB RAM/node. Cray Aries interconnect. 11 PB of high-performance storage.
CSCS – Swiss National Supercomputing Centre
CSCS Piz Daint 27 PF, 5704 nodes, Cray XC50/NVIDIA PASCAL
Xeon E5-2690v3 12C 2.6GHz 64GB RAM
NVIDIA® Tesla® P100 16GB
Aries interconnect
Swedish National Infrastructure for Computing (SNIC)

The Swedish National Infrastructure for Computing is a national research infrastructure that makes resources for large scale computation and data storage available, as well as provides advanced user support to make efficient use of the SNIC resources.

Beskow | 2.5 PF, 2060 nodes, Intel Haswell & Broadwell.

Funded by Swedish National Infrastructure for Computing and operated by the PDC Center for High-Performance Computing at the KTH Royal Institute of Technology in Stockholm, Sweden, Beskow supports capability computing and simulations in the form of wide jobs. Attached to Beskow is a 5 PB Lustre file system from DataDirect Networks. Beskow is also a Tier-1 resource in the Prace European Project.

Beskow is built by Cray, Intel and DataDirect Networks.

Korea Institute of Science and Technology Information (KISTI)

The Korea Institute of Science and Technology Information (KISTI) serves as a national supercomputing center of Korea, providing supercomputing and high-performance research networking facilities to Korean researchers. Together, with our hope to help accelerate the understanding of the COVID-19 virus for development of treatments and vaccines, KISTI is intended to contribute to the HPC Consortium of COVID-19 by offering access to the KISTI-5 supercomputer called Nurion. KISTI has also had a great experience in participating to the European project called WISDOM, a grid-enabled drug discovery initiative against malaria, several years ago in the era of Grid computing, where two teams in Korea joined the WISDOM collaboration by (1) offering computing resources along with relevant technology and (2) in-vitro testing to the initiative, respectively. KISTI still maintains the technology ( to facilitate the conducting of large-scale virtual screening experiments to identify small molecule drug candidates on top of multiple computing platforms.

Nurion | 25.7PF, 8437 nodes, Cray CS500

  • 8305 nodes Intel Xeon Phi 7250 (KNL) 68C 1.4GHz
    • 96GB DDR4 and 16 GB MCDRAM memory per KNL node
  • 132 nodes 2 x Intel Xeon 6148 (Skylake) 20C 2.4GHz
    • 192GB DDR4 memory per Skylate node  
  • 0.8PB DDN IME flash storage (burst buffer)
  • 20PB Lustre Filesystem
  • 10PB IBM TS 4500 Tape Storage 
  • Intel Omni-Path, Fat-Tree, 50% Blocking
Ministry of Education, Culture, Sports, Science and Technology(MEXT)-JAPAN

The supercomputer Fugaku is Japan's flagship supercomputer, developed mainly via collaboration between RIKEN Center for Computational Science (R-CCS) and Fujitsu, and to be commissioned for operation in 2021; however, portions of its resources is being deployed a year in advance to combat COVID-19. The technical specifications of Fugaku are as follows:

Fugaku | 89 PF, 26,496 nodes

  • Total # Nodes: 158,976 nodes
  • Processor core ISA: Arm (Aarch64 v8 + 512 bit SVE)
    • 48 + 2 or 4 cores per CPU chip, one CPU chip per node
  • ~400Gbps Tofu-D interconnect.
  • Theoretical Peak Compute Performances: Boost Mode (CPU Frequency 2.2GHz)
    • 64 bit Double Precision FP: 537 Petaflops
    • 32 bit Single Precision FP: 1.07 Exaflops
    • 16 bit Half Precision FP (AI training): 2.15 Exaflops
    • 8 bit Integer (AI Inference): 4.30 Exaops
  • Theoretical Peak Memory Bandwidth: 163 Petabytes/s
  • Approximately 150 Petabytes of Lustre storage
  • System software: Red Hat Enterprise Linux, all standard programming languages, optimized numerical libraries, MPI, OpenMP, TensorFlow/PyTorch, etc.

For details refer to:

Consortium Affiliates provide a range of computing services and expertise that can enhance and accelerate the research for fighting COVID-19. Matched proposals will have access to resources and help from Consortium Affiliates, provided for free, enabling rapid and efficiently execution of complex computational research programs.

Atrio | [Affiliate]

Atrio will assist researchers studying COVID-19 in creating and optimizing performance of application containers (e.g. CryoEM processing application suite) , as well as performance-optimized deployment of those application containers on to any of HPC Consortium members' computational platforms and specifically onto high performing GPU and CPU resources. Our proposal is two fold - one is additional computational resources, and another, equally important, is support for COVID-19 researchers with an easy way to access and use HPC Consortium computational resources. That support consists of creating application containers for researchers, optimizing their performance, and an optional multi-site container and cluster management software toolset.

Data Expedition Inc | [Affiliate]

Data Expedition, Inc. (DEI) is offering free licenses of its easy-to-use ExpeDat and CloudDat accelerated data transport software to researchers studying COVID-19. This software transfers files ranging from megabytes to terabytes from storage to storage, across wide area networks, among research institutions, cloud providers, and personal computers at speeds many times faster than traditional software. Available immediately for an initial 90-day license. Requests to extend licenses will be evaluated on a case-by-case basis to facilitate continuing research..

Flatiron | [Affiliate]

The Flatiron Institute is a multi-disciplinary science lab with 50 scientists in computational Biology. Flatiron is pleased to offer 3.5M core hours per month on our modern HPC system and 5M core hours per month on Gordon, our older HPC facility at SDSC.

Fluid Numerics | [Affiliate]

Fluid Numerics' Slurm-GCP deployment leverages Google Compute Engine resources and the Slurm job scheduler to execute high performance computing (HPC) and high throughput computing (HTC) workloads. Our system is currently capable of ~6pflops but please keep in mind this is a quota-bound metric that can be adjusted if needed. We intend to provide onboarding and remote system administration resources for the fluid-slurm-gcp HPC cluster solution on Google Cloud Platform. We will help researchers leverage GCP for COVID-19 research by assisting with software installation and porting, user training, consulting, and coaching, and general GCP administration, including quota requests, identity and access management, and security compliance.

SAS | [Affiliate]

SAS is offering to provide licensed access to the SAS Viya platform and data science project based resources. SAS provided resources will be specific to the requirements of the selected COVID-19 project use-case. SAS expects a typical engagement on a project would require 1-2 data science resources, a project manager, a data prep specialist and potentially a visualization expert.

Raptor Computing Systems, LLC | [Affiliate]

Our main focus for this membership though is developer systems, as we offer a wide variety of desktop and workstation systems built on the POWER architecture. These run Linux, support NVIDIA GPUs and provide an applications development environment for targeting the larger supercomputers. This is the main focus of our support effort. We can provide these machines free of charge (up to a reasonable limit) to the COVID effort to free up supercomputer / high end HPC server time that would otherwise be allocated to development and testing of the algorithms / software in use.

Mathworks | [Affiliate]

MathWorks will help researchers studying COVID-19 to scale their parallel MATLAB algorithms to the cloud and to HPC resources provided by this HPC Consortium. Our offering includes:

·  Free access to MATLAB® and Simulink® on the allocated computing resources.

·  Support for parallelizing and scaling researcher's algorithms.

As an example, see Ventilator research at Duke University.

The HDF Group | [Affiliate]

The HDF Group helps scientists use open source HDF5 effectively, including offering general usage and performance tuning advice, and helping to troubleshoot any issues that arise. Our engineers will be available to assist you in applying HPC and HDF® technologies together for your COVID-19 research.

Immortal Hyperscale InterPlanetary Fabrics | [Affiliate]

Immortal is providing licensed access to components of its platform to organizations which are (a) investigating the nature of the COVID-19 virus, (b) developing products for therapeutic breakthroughs, and (c) conducting R&D to build COVID-19 vaccines. Immortal's platform aggregates and orchestrates large magnitudes of applications, services, data, and resources across multiple Clouds, multiple supercomputers, or a combination. The platform is suitable for organizations operating on problems which need computation and data management at scales of hundreds of petaflops and hundreds of petabytes.

Acknowledging Support

Papers, presentations, and other publications featuring work that was supported, at least in part, by the resources, services and support provided via the COVID-19 HPC Consortium are expected to acknowledge that support.  Please include the following acknowledgement:

This work used resources services, and support provided via the COVID-19 HPC Consortium (, which is a unique private-public effort to bring together  government, industry, and academic leaders who are volunteering free compute time and resources in support of COVID-19 research.


(Revised 6 May 2022)

Key Points
Computing Resources utilized in research against COVID-19
National scientists encouraged to use computing resources
How and where to find computing resources
Contact Information