Associate Laboratory Director – Computing, Environment and Life Sciences / Professor of Computer Science, Argonne National Laboratory / University of Chicago.
Overview of HPC and AI Computing for COVID-19 in the US
In this talk I’ll describe some of the ongoing work in the US applying HPC and AI to COVID-19 related research. I will discuss two activities launched in the spring of 2020, the first is the COVID-19 HPC consortium that joins US supercomputing centers, computing and technology vendors and federal agencies to provide HPC cycles to the SARS- CoV-2/COVID-19 research community and to streamline access to resources via a single proposal mechanism. Currently the HPC consortium has 40 members, access to over 136K nodes, 5M CPUS and 50K GPUs totaling more than 558 Petaflops and is supporting 66 peer reviewed research projects related to the pandemic. The second topic I’ll discuss is the nine DOE laboratory collaboration (Argonne, Berkeley, Brookhaven, Oak Ridge, Livermore, Los Alamos, Pacific Northwest, Sandia and SLAC) formed to apply advanced computing to the problem of developing molecular therapeutics for COVID-19. This project is one of part of the DOE sponsored National Virtual BioTechnology Laboratory (NVBTL) formed to coordinate national laboratory efforts related to the pandemic. For each of these I’ll give a brief overview of the science, the state of play and how HPC and AI are being used and progress towards solutions.
My research spans the computational and computer sciences from high-performance computing, to the building of innovative tools and techniques for biological science and infectious disease research as well approaches to advance deep learning to accelerate cancer research and COVID-19 research. I also specialize in high-performance computing, collaborative visualization technology, and grid computing. At Argonne, I lead the Laboratory’s AI for Science initiative and currently focusing on high-performance computing systems which includes collaborating with Intel and Cray to launch Argonne’s first exascale computer, Aurora 21, as well as the partnership with Cerebras Systems that brought hardware on site to advance the deep learning experiments being pursued at Argonne for basic and applied science and medicine with supercompute-scale AI.