BP Supercomputer to Aid COVID-19 Researchers
BP has joined a public-private consortium, which includes the U.S. government, universities and the world’s largest technology companies, to help researchers halt the spread of COVID-19.
BP is donating its significant supercomputing capability to the cause.
The consortium was formed in March 2020 by the White House’s Office of Science and Technology Policy, the U.S. Department of Energy and IBM. The group, known as the COVID-19 High Performance Computing Consortium, will pool resources and expertise from Amazon Web Services, Google Cloud, Microsoft, Hewlett Packard Enterprise, BP and others. The aim is to provide COVID-19 researchers worldwide with access to the most powerful high-performance computing resources to advance the pace of scientific discovery in the fight to stop the virus.
BP will provide access to its Center for High-Performance Computing (CHPC) in Houston, which houses one of the world’s largest supercomputers for commercial research and processes enormous amounts of data for BP. It has 16.3 petaflops of computing capability, allowing it to process more than 16 million billion calculations per second and complete a problem in an hour that would take a laptop nine years. The Center’s staff includes experts in data science, applied mathematics and systems architecture.
BP will also make available the expertise of its Biosciences Center, located in San Diego, California. The center consists of dozens of scientists who have capabilities in biological sciences, chemical engineering and chemistry.
The sophisticated computing systems available through this consortium can process massive numbers of calculations related to bioinformatics, epidemiology, and molecular modeling, expected to help scientists develop answers to complex scientific questions about COVID-19 in hours or days versus weeks or months.
Among the proposals accepted by the consortium is one that will use artificial intelligence-driven biology to discover a treatment against COVID-19. A team, led by computational biologist Arvind Ramanathan of Argonne National Laboratory, aims to address the fundamental biological mechanisms of the virus and the disease and to identify potential therapeutics – with the help of machine learning and deep learning.
A similar proposal comes from a Germany-headquartered AI company Innoplexus. Here, the researchers’ goal is to use deep learning to generate novel molecules to create a new drug.
Another project is examining the origin and evolutionary history of the disease-causing virus, SARS-CoV-2 - something that is still unclear. A voluntarily interdisciplinary team of more than 10 scientists in the U.S. and across the globe, with expertise in phylogenomics, population genetics, quantitative genetics, microbiology, and software engineering, are tackling the problem by leveraging the publicly available genome assemblies of SARS-CoV-2 as well as patient metadata to investigate the evolutionary and divergence pattern of the virus.
In the past, the coronavirus family of viruses such as SARS and MERS have gradually disappeared in the hot and humid conditions. Data obtained from countries with higher temperature and humidity also indicate a low propensity of infection. In another project, the impact of atmospheric conditions, mainly the temperature and humidity, is being investigated to determine if the virus undergoes any biophysical changes with change in atmospheric conditions. Molecular dynamics simulations are being used in the work.
Amazon Web Services
Hewlett Packard Enterprise
Massachusetts Institute of Technology
Rensselaer Polytechnic Institute
University of Illinois
University of Texas at Austin
University of California - San Diego
Carnegie Mellon University
University of Pittsburgh
University of Wisconsin-Madison
Department of Energy National Laboratories
Argonne National Laboratory
Lawrence Livermore National Laboratory
Los Alamos National Laboratory
Oak Ridge National Laboratory
National Energy Research Scientific Computing Center
Sandia National Laboratories
National Science Foundation
Pittsburgh Supercomputing Center (PSC)
Texas Advanced Computing Center (TACC)
San Diego Supercomputer Center (SDSC)
National Center for Supercomputing Applications (NCSA)
Indiana University Pervasive Technology Institute (IUPTI)
Open Science Grid (OSG)
National Center for Atmospheric Research (NCAR)