DOE provides more detail on COVID-19 supercomputing consortium

After announcing the launch of the COVID-19 High Performance Computing Consortium on Sunday, the Department of Energy yesterday provided more details on its scope and operation in a briefing led by Undersecretary of Energy Paul Dabbar and attended by HPC leaders from national labs. The joint public-private effort will pool 16 systems which together offer more than 330 petaflops along with extensive cloud resources. A portal has been set up to receive COVID-19 project proposals.

This excerpt is from the portal:

“Researchers are invited to submit COVID-19 related research proposals to the consortium via this online portal, which will then be reviewed for matching with computing resources from one of the partner institutions. An expert panel comprised of top scientists and computing researchers will work with proposers to assess the public health benefit of the work, with emphasis on projects that can ensure rapid results.
“Fighting COVID-19 will require extensive research in areas like bioinformatics, epidemiology, and molecular modeling to understand the threat we’re facing and form strategies to address it. This work demands a massive amount of computational capacity. The COVID-19 High Performance Computing Consortium helps aggregate computing capabilities from the world’s most powerful and advanced computers to help COVID-19 researchers execute complex computational research programs to help fight the virus.”

Key government partners so far include Argonne National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratories, National Science Foundation, and NASA. Among industry partners are IBM, HPE, Amazon Web Services, Google Cloud, and Microsoft. A few examples from academia include MIT, Rensselaer Polytechnic Institute, University of Chicago, and Northwestern University.

As explained by Dabbar, the current plan is to reallocate resources (compute cycles and expertise) rather than attempt to acquire and stand-up new resources. That said, additional resources could be made available as they come online.

Systems will include leadership platforms such as Summit (ORNL) currently the fastest supercomputer in the world (Top500 List, Nov. 2019) and Sierra (LLNL). In fact, several COVID-19 projects are already underway. Dabbar referenced an Oak Ridge National Lab project in which researchers explored 8000 compounds of interest narrowing that to 77 promising small molecule drug compounds. Not surprisingly the early COVID-19 drug research is focused on already approved drugs (~10,000) because they have already passed safety hurdles and more is known about them.

It’s worth noting that DoE and other government agencies already have aggressive computational life science projects. The CANDLE project being run by the National Cancer Institute is a good example. It’s focused on building machine learning tools for use in cancer research. There’s also the ATOM (Accelerating Therapeutics for Opportunities in Medicine) project at LLNL. Both CANDLE and ATOM are pivoting efforts toward COVID-19.

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