In June 2018, the U.S. Department of Energy’s Oak Ridge National Laboratory unveiled the IBM-built Summit as the most powerful and smartest scientific supercomputer. With a peak performance of 200,000 trillion calculations per second—or 200 petaflops, Summit is eight times more powerful than Oak Ridge National Laboratory’s previous top-ranked system, Titan.
Since it debuted in 2018, Summit has driven groundbreaking research from helping to understand the origins of the universe, helping to understand the opioid crisis, and showing how humans would be able to land on Mars.
Recently, the energy department and IBM joined the fight against the COVID-19 pandemic with the supercomputer. According to Dave Turek, vice president of technical computing at IBM Cognitive Systems, Summit researchers were able to simulate a model that could impact the infection process by binding to the virus’s spike.
They have also identified medications and natural compounds that have shown the potential to impair COVID-19’s ability to dock with and infect host cells.
“Summit was needed to rapidly get the simulation results we needed. It took us a day or two whereas it would have taken months on a normal computer,” said Jeremy Smith, director of the University of Tennessee/Oak Ridge National Laboratory Center (ORNL) for Molecular Biophysics, and principal researcher in the study.
“Our results don’t mean that we have found a cure or treatment for COVID-19. We are very hopeful, though, that our computational findings will both inform future studies and provide a framework that experimentalists will use to further investigate these compounds. Only then will we know whether any of them exhibit the characteristics needed to mitigate this virus.”
Turek said the hope is to see how Summit can continue to lend its weight in this latest pursuit. Click here to read more.
Viruses infect cells by binding to them and using a ‘spike’ to inject their genetic material into the host cell. When trying to understand new biological compounds, like viruses, researchers in wet labs grow the micro-organism and see how it reacts in real-life to the introduction of new compounds, but this can be a slow process without computers that can perform digital simulations to narrow down the range of potential variables, but even then there are challenges.
Computer simulations can examine how different variables react with different viruses, but when each of these individual variables can be comprised of millions or even billions of unique pieces of data and compounded with the need to be run multiple simulations, this can quickly become a very time-intensive process using commodity hardware.