2022 Readers’ & Editors’ Choice Awards – Best HPC Response to Societal Plight

Best HPC Response to Societal Plight

(Urgent Computing, COVID-19)

Readers’ Choice Awards

When Paxlovid was still being vetted, a team of researchers from the University of Valencia applied supercomputing power to determine how, exactly, the drug inhibits SARS-CoV-2. Paxlovid works by binding to SARS-CoV-2’s 3CL protease (3CLpro), an enzyme that serves as a crucial piece of the virus’ replication process. The researchers used a computational hybrid methodology that combines classical molecular dynamics with quantum mechanics. They ran those simulations on the MareNostrum 4 supercomputer (built by Lenovo leveraging Intel technologies) at the Barcelona Supercomputing Center. The simulations illuminated exactly why Paxlovid is so effective in debilitating SARS-CoV-2. And the researchers were able to produce a visualization of Paxlovid inhibiting the virus.

Editors’ Choice Awards

TIE

Researchers from the University of California Riverside (UCR), using supercomputing power at the San Diego Supercomputer Center, investigated methods of removing nonbiodegradable “forever chemicals” like perfluoroalkyl and polyfluoroalkyl substances (collectively, PFASs) from drinking water – one of their primary methods of ingress to the human body. The researchers used simulations to explore the ability of light to degrade these chemicals. To run the simulations, they used the San Diego Supercomputer Center’s Comet supercomputer, a 2.76-peak petaflops system, supplied by Dell. They found that bombarding virtual PFASs with virtual light dissolved the PFASs into virtual water molecules. Understanding the process at a quantum-mechanical level will help design ways to treat PFASs in the future.

TIE

Researchers at the San Diego Supercomputer Center and UC San Diego, in partnership with San Diego County’s Health and Human Services Agency (HHSA), developed computational tools that help the county plan for Covid-safe school operations. At the heart of the effort is the Geographically assisted Agent-based model for COVID-19 Transmission (GeoACT), which was designed for use on the center’s Comet and Expanse supercomputers (both built by Dell). The simulations run by the group using the model allow researchers to pinpoint areas in schools that would present higher COVID-19 transmission risks and evaluate the relative importance of non-pharmaceutical interventions, such as wearing masks, reducing class sizes, or moving lunch from the cafeteria into classrooms.

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