Q&A with Under Secretary Paul Dabbar on the COVID-19 High Performance Computing Consortium

Currently, six DOE National Labs are involved in the Consortium: Argonne, Lawrence Berkeley, Lawrence Livermore, Los Alamos, Oak Ridge, and Sandia National Laboratories.  

The DOE National Laboratories selected have world leading supercomputing capabilities that are uniquely suited to performing complex simulations, which are increasingly employing machine learning and artificial intelligence as a critical component of the model. It is this capability that DOE will use to address the COVID-19 challenges. 

DOE is already using AI to search for drugs that might be effective on the virus, to identify those proteins in both the virus and in the host that will be good drug targets, to look for important mutations related to vaccine development and drug targeting, and to highlight effective strategies to minimize the load on the health care system and maximize the protection to vulnerable groups. This effort is enabled by work our labs have been doing for several years leveraging AI in the fight against cancer. The lessons learned from that work have been quickly transitioned to support similar efforts for COVID-19.

The combination of DOE supercomputers with the increasing expertise at the DOE laboratories for incorporating AI into scientific research can be of great service in this battle. Working with   pharmaceutical and diagnostics companies, DOE is accelerating the discovery of promising treatments. Working with policy makers, we are devising effective ways to manage the course of infection and deploy much needed resources strategically, to the locations where they will do the most good.

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