Ten organizations have created a pipeline of artificial intelligence and simulation tools to narrow the search for drug candidates that can inhibit SARS-CoV-2.
The research described in the winning paper is focused on using a high-performance, iterative reconstruction system for noninvasive imaging at synchrotron facilities.
To leverage emerging computing capabilities and prepare for future exascale systems, the Argonne Leadership Computing Facility, a DOE Office of Science User Facility, is expanding its scope beyond traditional simulation-based research to include data science and machine learning approaches.
A collaboration between the University of Cambridge and Argonne has developed a unique method of generating automatic databases to support specific fields of science using AI and high-performance computing.
Argonne scientists are working around the clock to analyze the virus to find new treatments and cures, predict how it will propagate through the population, and make sure that our supply chains remain intact.