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The Fastest Supercomputer on Earth Is Being Deployed Against Coronavirus

Credit: Carlos Jones/ORNL, CC BY 2.0

The US Department of Energy has announced that the Summit supercomputer will be used to attempt to find a treatment or cure for Covid-19, also known as coronavirus. Summit is a 10MW machine built with 4,608 processing nodes. Each node contains 2x Power9 CPUs at 3.07GHz and six Nvidia Volta V100 GPUs. It’s the fastest supercomputer on Earth, with a demonstrated performance of 148.6 petaFLOPS in Linpack and peak performance of over 200 petaFLOPS.

The reason the DoE is tapping the world’s fastest supercomputer for the project is that trying to find methods of inhibiting or attacking a virus is a computationally taxing problem. IBM writes:

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.

The video below summarizes the work scientists have done using Summit. Thanks to the supercomputer, researchers screened 8,000 compounds in a matter of days and identified 77 potentially beneficial small-molecule compounds that show evidence of inhibiting Covid-19.

“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, Governor’s Chair at the University of Tennessee, director of the UT/ORNL Center 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.”

If you’ve read that Covid-19 is similar to SARS in some respects, early investigations of the virus are what led to that conclusion. SARS and coronavirus share some common infection strategies, which has led to some hope that an inhibitory agent can be found. Using Summit, Micholas Smith (not a typo) tested how compounds bonded to the S-protein “spike” to discover which might reduce the chance of successful infection. Since that initial work was done, a more accurate model of the S-protein in coronavirus has been released. The team using Summit is planning to re-run their initial analysis using the more detailed model, which may prune some compounds off the list or vault others to the top.

The scientists have emphasized that all of their work must be tested experimentally, but we have now seen some evidence that computers can be helpful for these kinds of calculations. Although it’s very early days, scientists have begun to discover new drug treatments through the use of machine learning.

The worldwide number of coronavirus has been growing at an accelerating rate since the virus escaped China. The best day for the virus since tracking began was February 19, when 516 new cases were logged. By February 28, we were up to 1,503 new cases. On March 10, 4,390 new cases of coronavirus were logged. The number of people infected per day by Covid-19 grew 2.92x in just 11 days. That’s much less bad than the apocalyptic scenarios typically envisioned in medical disaster movies, but it’s still a high rate of growth. If it continues, we’d be looking at 12,822 new cases per day by March 22 and 37,441 new cases per day by April 2.

The good news, however, is that the overall number of severe/serious cases continues to drop in absolute terms. According to, which seems to be maintaining up-to-date daily tracking, the total number of severe/serious cases fell from 11,553 on February 22 to 5,771 on March 10. There’s been only one day in-between where the number of serious cases ticked upwards and it was a small jump, from 6,272 to 6,401. The numbers have resumed their downward decline.

The question of whether Covid-19 is going to have a significant impact on the world economy has already been answered: yes. No matter what happens now, Q1 figures are going to be wrecked across the board. A number of major conferences have been canceled, depriving local communities of income. Airlines are reporting high declines in flying comparable to the hit they took after 9/11. With Chinese factories shut down for weeks, the entire country of Italy under quarantine, and tens of millions of people now practicing social distancing (voluntarily or otherwise), the question of whether we’re going to feel the impact in the United States is clear: We are. It may take time to arrive — the economic impact of events on distant shores can travel at varying speeds — but the slowdowns and cancellations are already hitting companies.

Does this mean you need to run out and buy two tons of disposable paper products? No. But it does mean that, one way or the other, Covid-19 is going to affect our lives to some degree. The oil war that kicked off between Russia and Saudi Arabia this week is an excellent example of how coronavirus could spark global recession even if the medical risk turns out to be smaller than thought. With the Russians and Saudis contributing to see who can charge less for oil, US shale oil production might have to stop if prices fall too far. That would have its own impact on the US economy as well.

Nobody knows where this train is headed yet, but we’re all aboard it together.

Update: Summit’s power draw was mistakenly listed as 10KW because I somehow meshed “10K” as in 10,000, and 10KW (as in power). Apologies for the mistake. Summit’s official power draw is 10,096kW according to the TOP500.

Top image credit: Carlos Jones/ORNL, CC BY 2.0

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