Gordon Bell Special Prize Goes to Massive SARS-CoV-2 Simulations

By Oliver Peckham

November 19, 2020

2020 has proven a harrowing year – but it has produced remarkable heroes. To that end, this year, the Association for Computing Machinery (ACM) introduced the Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. The prize, which was awarded in a ceremony today at the (virtual) SC20 supercomputing conference, recognizes “outstanding research achievement towards the understanding of the COVID-19 pandemic through the use of high-performance computing.” 

Nominations for the prestigious award were selected “based on performance and innovation in their computational methods, in addition to their contributions towards understanding the nature, spread and/or treatment of the disease.” The award is accompanied by a $10,000 prize. The Special Prize for High Performance Computing-Based COVID-19 Research is slated to be awarded in 2021 as well.

The four finalist teams presented virtually at SC20 in advance of the awards ceremony, showcasing the myriad ways in which massive supercomputing has been utilized to provide crucial knowledge around the pandemic and the virus at its core, from atom-by-atom simulations of the viral envelope to person-by-person simulations of major cities.

And the winner is…

Bronis R. de Supinski, chair of the Gordon Bell Prize Committee and CTO for Livermore Computing at Lawrence Livermore National Laboratory (LLNL), took the virtual stage to announce the winning team: a wide-reaching, nationwide collaboration to develop unprecedented simulations of key aspects of the novel coronavirus.

Image courtesy of SC20

AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics

Team: Lorenzo Casalino, Abigail Dommer, Zied Gaieb, Emilia P. Barros, Terra Stzain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony Bogetti, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian Chong, Carlos Simmerling, David Hardy, Julio Maia, James Phillips, Thorsten Kurth, Abraham Stern, Lei Huang, John McCalpin, Mahidhar Tatineni, Tom Gibbs, John Stone, Shantenu Jha, Arvind Ramanathan and Rommie E. Amaro.

The winning team zeroed in on a part of the SARS-CoV-2 virus that has become notorious to anyone following COVID-19 research: the spike protein, which both provides the coronavirus with its namesake crown-like spikes and allows it to infect human cells. The team used Summit (still the second-most powerful publicly ranked supercomputer) to simulate the SARS-CoV-2’s spike protein and viral envelope using 305 million atoms.

The resulting model of SARS-CoV-2. Image courtesy of Rommie Amaro and Lorenzo Casalino.

“Experiments give us a picture of what these things look like, but they can’t tell us the whole story,” said Rommie Amaro, co-lead of the project and professor and endowed chair of chemistry and biochemistry at the University of California San Diego. “The only way we can do this is through simulations, and right now we are pushing the capabilities of molecular simulations to the limits of the computer architectures that we have on this earth. This is at the edge of possibilities of what people are capable of doing.”


“We are giving people never-before-seen, intimate views of this virus, with resolution that is impossible to achieve experimentally.”


“We are giving people never-before-seen, intimate views of this virus, with resolution that is impossible to achieve experimentally,” she added. “Why we care about this is because if we want to understand how the virus infects the host cell, if we want to be able to design antibodies and new drugs to block and cure infection, if we want to be able to design new therapeutics, this information at this very fine resolution at the atomic level is required.”

To achieve the massive simulation, the team optimized and scaled the Nanoscale Molecular Dynamics (NAMD) code across Summit, a feat made possible through extensive work on other supercomputers, including Frontera, Comet and ThetaGPU. The results illuminated the virus’ sugary glycan shield – which protects it from many pharmaceutical attack strategies – and highlighted the critical role of the virus’ receptor binding domain.


An incredible slate of finalists

Though the SARS-CoV-2 simulations took home the prize at the end of the day, the entire field of finalists illustrated the astonishing work that the HPC community has put into ending the pandemic. Keep reading to learn more about the other three finalist teams.

High-Throughput Virtual Laboratory for Drug Discovery Using Massive Datasets

Team: Jens Glaser, Josh V. Vermaas, David M. Rogers, Jeff Larkin, Scott LeGrand, Swen Boehm, Matthew B. Baker, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Ada Sedova and Oscar Hernandez.

Another ORNL-based team also used Summit – this time, to screen more than a billion compounds for their ability to bind with two different structures of SARS-CoV-2’s main protease… and completing each of those screenings in under 24 hours. 

To achieve those remarkable results, the team scaled AutoDock-GPU to 27,612 of Summit’s Nvidia V100 GPUs, ending up with a 350-fold speedup compared to the CPU version of the same code. The researchers faced an uphill battle on this front, as very few molecular docking codes have used GPUs, and fewer still are well-supported – let alone open-source. The researchers worked with Nvidia to create a CUDA version of the code for high-throughput analysis.


“When we were using Summit, we were docking 20,000 compounds a second.”


“When we were using Summit, we were docking 20,000 compounds a second,” said Ada Sedova, a biophysicist in the Molecular Biophysics Group within ORNL’s Biosciences Division and co-lead of the project. “We have done this in 24 hours with full optimization of these poses, the way people would normally do at the small scale. To be able to do this on a billion compounds would have taken months on even the largest academic clusters without the optimizations of AutoDock-GPU for Summit.”

An illustration of how small molecules can occupy spaces in SARS-CoV-2’s viral proteins. Image courtesy of Joshua Vermaas.

“We think that the rapid response to the COVID-19 pandemic that we stood up on Summit is essential to developing a forward-looking computational capability for future global health crises,” added Jens Glaser, a computational scientist at ORNL and another co-lead of the project. “Importantly, the speedup was realized end-to-end and contains necessary machine learning and data analytics components, and that allows us to incorporate feedback from experiments into the machine learning models and converge onto predictions and more potent inhibitors.”

A Population Data-Driven Workflow for COVID-19 Modeling and Learning

Team: Jonathan Ozik, Justin M. Wozniak, Nicholson Collier, Charles M. Macal and Mickael Binois.

A finalist team led by Argonne National Laboratory, meanwhile, used supercomputing for epidemiological analysis. Using Argonne’s Theta supercomputer (39th on the most recent Top500), the team modeled how COVID-19 spreads through populations using a city-scale representation of Chicago. The simulated Windy City was populated by 2.7 million digital individuals traveling among 1.2 million locations. The model was optimized to simultaneously run on more than 800 of Theta’s nodes.

Mobility patterns generated by the CityCOVID model. Image courtesy of Argonne.

“In ChiSIM [the Chicago Social Interaction Model], we represent every person in the city of Chicago as an individual, including their socioeconomic and demographic variables, their activities and the places they visit – schools and workplaces, for example – in the course of those activities,” explained Nicholson Collier, a senior software engineer at Argonne. “As the agents follow their activity schedules, they become colocated with other agents in a place and interact with them, leading to trillions of interactions over the course of the simulation.”


“… trillions of interactions over the course of the simulation.”


“With this model, you have potentially many people interacting in many different ways: some might be infected, some might be susceptible, and they mix in different proportions in a variety of different locations – there are different locations like schools and workplaces where very different parts of the population interface,” said Jonathan Ozik, an Argonne computational scientist and co-lead of the project. ​“The multitude of possibilities the model presents make it quite qualitatively different from – and quantitatively more complex than – a statistical model or more simplified compartmental models, which are much faster to run.”

Throughout the pandemic, results from CityCOVID have been used to inform stakeholders and decision-makers, particularly in Chicago and the state of Illinois.

Enabling Rapid COVID-19 Small Molecule Drug Design Through Scalable Deep Learning of Generative Models

Team: Sam Ade Jacobs, Tim Moon, Kevin McLoughlin, William D. Jones, David Hysom, Dong H. Ahn, John Gyllenhaal, Pythagoras Watson, Felice C. Lightstone, Jonathan E. Allen, Ian Karlin and Brian Van Essen.

Another finalist team hailed from LLNL, where researchers used Sierra (which recently defended its title as the 3rd most powerful publicly ranked supercomputer) to create an accurate, efficient generative model for producing novel compounds with the potential to treat COVID-19. After training the model on over 1.6 billion small molecule compounds, the team reduced the training time from a day to just 23 minutes.

“Drug design is both costly in time and effort,” said Brian Van Essen, a computer scientist and leader of the Informatics Group at LLNL. “It’s normally a 15-year process to bring a new therapeutic from discovery all the way through FDA review.” The goal, he said, was to greatly condense the time frame of the first two trial phases, but also reduce the high risk of failure in phase three trials.

The pharmaceutical pipeline. Image courtesy of the researchers.

“Our globally asynchronous multi-level parallel training approach strong scales to all of Sierra with up to 97.7 percent efficiency,” the researchers wrote, adding that they achieved 318 petaflops for 17.1 percent of half-precision peak using tensor cores. The researchers say that their model can be used to create an automated “self-learning design loop” for drug discovery, even with much less impressive computing resources than Sierra.


“This ability to quickly create high-quality machine learning models changes the time-to-insight from a compute-limited issue to a human-limited one.”


“This capability will have a dramatic impact on drug discovery,” said Ian Karlin, an LLNL computer scientist who co-authored the paper. “This ability to quickly create high-quality machine learning models changes the time-to-insight from a compute-limited issue to a human-limited one.”

Next, the researchers want to improve the scaling even further, train using more types of models, increase automation and improve overall efficiency.

And also…

Don’t forget to check our coverage of the winners and finalists for the 2020 ACM Gordon Bell Prize.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

University of Chicago Researchers Generate First Computational Model of Entire SARS-CoV-2 Virus

January 15, 2021

Over the course of the last year, many detailed computational models of SARS-CoV-2 have been produced with the help of supercomputers, but those models have largely focused on critical elements of the virus, such as its Read more…

By Oliver Peckham

Pat Gelsinger Returns to Intel as CEO

January 14, 2021

The Intel board of directors has appointed a new CEO. Intel alum Pat Gelsinger is leaving his post as CEO of VMware to rejoin the company that he parted ways with 11 years ago. Gelsinger will succeed Bob Swan, who will remain CEO until Feb. 15. Gelsinger previously spent 30 years... Read more…

By Tiffany Trader

Roar Supercomputer to Support Naval Aircraft Research

January 14, 2021

One might not think “aircraft” when picturing the U.S. Navy, but the military branch actually has thousands of aircraft currently in service – and now, supercomputing will help future naval aircraft operate faster, Read more…

By Staff report

DOE and NOAA Extend Computing Partnership, Plan for New Supercomputer

January 14, 2021

The National Climate-Computing Research Center (NCRC), hosted by Oak Ridge National Laboratory (ORNL), has been supporting the climate research of the National Oceanic and Atmospheric Administration (NOAA) for the last 1 Read more…

By Oliver Peckham

Using Micro-Combs, Researchers Demonstrate World’s Fastest Optical Neuromorphic Processor for AI

January 13, 2021

Neuromorphic computing, which uses chips that mimic the behavior of the human brain using virtual “neurons,” is growing in popularity thanks to high-profile efforts from Intel and others. Now, a team of researchers l Read more…

By Oliver Peckham

AWS Solution Channel

Now Available – Amazon EC2 C6gn Instances with 100 Gbps Networking

Amazon EC2 C6gn instances powered by AWS Graviton2 processors are now available!

Compared to C6g instances, this new instance type provides 4x higher network bandwidth, 4x higher packet processing performance, and 2x higher EBS bandwidth. Read more…

Intel® HPC + AI Pavilion

Intel Keynote Address

Intel is the foundation of HPC – from the workstation to the cloud to the backbone of the Top500. At SC20, Intel’s Trish Damkroger, VP and GM of high performance computing, addresses the audience to show how Intel and its partners are building the future of HPC today, through hardware and software technologies that accelerate the broad deployment of advanced HPC systems. Read more…

Honing In on AI, US Launches National Artificial Intelligence Initiative Office

January 13, 2021

To drive American leadership in the field of AI into the future, the National Artificial Intelligence Initiative Office has been launched by the White House Office of Science and Technology Policy (OSTP). The new agen Read more…

By Todd R. Weiss

Pat Gelsinger Returns to Intel as CEO

January 14, 2021

The Intel board of directors has appointed a new CEO. Intel alum Pat Gelsinger is leaving his post as CEO of VMware to rejoin the company that he parted ways with 11 years ago. Gelsinger will succeed Bob Swan, who will remain CEO until Feb. 15. Gelsinger previously spent 30 years... Read more…

By Tiffany Trader

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

By John Russell

Intel ‘Ice Lake’ Server Chips in Production, Set for Volume Ramp This Quarter

January 12, 2021

Intel Corp. used this week’s virtual CES 2021 event to reassert its dominance of the datacenter with the formal roll out of its next-generation server chip, the 10nm Xeon Scalable processor that targets AI and HPC workloads. The third-generation “Ice Lake” family... Read more…

By George Leopold

Researchers Say It Won’t Be Possible to Control Superintelligent AI

January 11, 2021

Worries about out-of-control AI aren’t new. Many prominent figures have suggested caution when unleashing AI. One quote that keeps cropping up is (roughly) th Read more…

By John Russell

AMD Files Patent on New GPU Chiplet Approach

January 5, 2021

Advanced Micro Devices is accelerating the GPU chiplet race with the release of a U.S. patent application for a device that incorporates high-bandwidth intercon Read more…

By George Leopold

Programming the Soon-to-Be World’s Fastest Supercomputer, Frontier

January 5, 2021

What’s it like designing an app for the world’s fastest supercomputer, set to come online in the United States in 2021? The University of Delaware’s Sunita Chandrasekaran is leading an elite international team in just that task. Chandrasekaran, assistant professor of computer and information sciences, recently was named... Read more…

By Tracey Bryant

Intel Touts Optane Performance, Teases Next-gen “Crow Pass”

January 5, 2021

Competition to leverage new memory and storage hardware with new or improved software to create better storage/memory schemes has steadily gathered steam during Read more…

By John Russell

Farewell 2020: Bleak, Yes. But a Lot of Good Happened Too

December 30, 2020

Here on the cusp of the new year, the catchphrase ‘2020 hindsight’ has a distinctly different feel. Good riddance, yes. But also proof of science’s power Read more…

By John Russell

Esperanto Unveils ML Chip with Nearly 1,100 RISC-V Cores

December 8, 2020

At the RISC-V Summit today, Art Swift, CEO of Esperanto Technologies, announced a new, RISC-V based chip aimed at machine learning and containing nearly 1,100 low-power cores based on the open-source RISC-V architecture. Esperanto Technologies, headquartered in... Read more…

By Oliver Peckham

Azure Scaled to Record 86,400 Cores for Molecular Dynamics

November 20, 2020

A new record for HPC scaling on the public cloud has been achieved on Microsoft Azure. Led by Dr. Jer-Ming Chia, the cloud provider partnered with the Beckman I Read more…

By Oliver Peckham

NICS Unleashes ‘Kraken’ Supercomputer

April 4, 2008

A Cray XT4 supercomputer, dubbed Kraken, is scheduled to come online in mid-summer at the National Institute for Computational Sciences (NICS). The soon-to-be petascale system, and the resulting NICS organization, are the result of an NSF Track II award of $65 million to the University of Tennessee and its partners to provide next-generation supercomputing for the nation's science community. Read more…

Is the Nvidia A100 GPU Performance Worth a Hardware Upgrade?

October 16, 2020

Over the last decade, accelerators have seen an increasing rate of adoption in high-performance computing (HPC) platforms, and in the June 2020 Top500 list, eig Read more…

By Hartwig Anzt, Ahmad Abdelfattah and Jack Dongarra

Aurora’s Troubles Move Frontier into Pole Exascale Position

October 1, 2020

Intel’s 7nm node delay has raised questions about the status of the Aurora supercomputer that was scheduled to be stood up at Argonne National Laboratory next year. Aurora was in the running to be the United States’ first exascale supercomputer although it was on a contemporaneous timeline with... Read more…

By Tiffany Trader

Google Hires Longtime Intel Exec Bill Magro to Lead HPC Strategy

September 18, 2020

In a sign of the times, another prominent HPCer has made a move to a hyperscaler. Longtime Intel executive Bill Magro joined Google as chief technologist for hi Read more…

By Tiffany Trader

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

By John Russell

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

By Doug Black

Leading Solution Providers

Contributors

Programming the Soon-to-Be World’s Fastest Supercomputer, Frontier

January 5, 2021

What’s it like designing an app for the world’s fastest supercomputer, set to come online in the United States in 2021? The University of Delaware’s Sunita Chandrasekaran is leading an elite international team in just that task. Chandrasekaran, assistant professor of computer and information sciences, recently was named... Read more…

By Tracey Bryant

Top500: Fugaku Keeps Crown, Nvidia’s Selene Climbs to #5

November 16, 2020

With the publication of the 56th Top500 list today from SC20's virtual proceedings, Japan's Fugaku supercomputer – now fully deployed – notches another win, Read more…

By Tiffany Trader

European Commission Declares €8 Billion Investment in Supercomputing

September 18, 2020

Just under two years ago, the European Commission formalized the EuroHPC Joint Undertaking (JU): a concerted HPC effort (comprising 32 participating states at c Read more…

By Oliver Peckham

Texas A&M Announces Flagship ‘Grace’ Supercomputer

November 9, 2020

Texas A&M University has announced its next flagship system: Grace. The new supercomputer, named for legendary programming pioneer Grace Hopper, is replacing the Ada system (itself named for mathematician Ada Lovelace) as the primary workhorse for Texas A&M’s High Performance Research Computing (HPRC). Read more…

By Oliver Peckham

At Oak Ridge, ‘End of Life’ Sometimes Isn’t

October 31, 2020

Sometimes, the old dog actually does go live on a farm. HPC systems are often cursed with short lifespans, as they are continually supplanted by the latest and Read more…

By Oliver Peckham

Nvidia and EuroHPC Team for Four Supercomputers, Including Massive ‘Leonardo’ System

October 15, 2020

The EuroHPC Joint Undertaking (JU) serves as Europe’s concerted supercomputing play, currently comprising 32 member states and billions of euros in funding. I Read more…

By Oliver Peckham

Gordon Bell Special Prize Goes to Massive SARS-CoV-2 Simulations

November 19, 2020

2020 has proven a harrowing year – but it has produced remarkable heroes. To that end, this year, the Association for Computing Machinery (ACM) introduced the Read more…

By Oliver Peckham

Nvidia-Arm Deal a Boon for RISC-V?

October 26, 2020

The $40 billion blockbuster acquisition deal that will bring chipmaker Arm into the Nvidia corporate family could provide a boost for the competing RISC-V architecture. As regulators in the U.S., China and the European Union begin scrutinizing the impact of the blockbuster deal on semiconductor industry competition and innovation, the deal has at the very least... Read more…

By George Leopold

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This