At SC20, an Expert Panel Braces for the Next Pandemic

By Oliver Peckham

November 17, 2020

COVID-19 isn’t over – not even close. With about six months until broad vaccine distribution is expected, the world will likely face a long, difficult winter before the pandemic begins to truly wane. Still, with the anniversary of the pandemic swiftly approaching, many in the scientific community are beginning to look back on the early months of COVID-19 to examine what worked (and what didn’t) when the world scrambled to respond to the global crisis. At SC20, four panelists gathered to discuss the roles HPC has played in this pandemic – and what will need to change for advanced computing to respond more successfully to the next one.

The panelists

The plenary session — titled “Advanced Computing and COVID-19: It’s More Than HPC” — featured four distinguished panelists.

Rommie Amaro is a professor and endowed chair of chemistry and biochemistry at the University of California, San Diego. She studies computational methods in biophysics, including work to develop the first complete all-atom model of SARS-CoV-2’s viral envelope.

Alessandro “Alex” Vespignani is a professor of physics and the director of the Network Science Institute at Northeastern University. Vespignani describes his technosocial research on COVID-19 as “what is done by numerical weather forecasting, but in the area of infectious diseases.”

Ilkay Altintas is a data and computer scientist who serves as the chief data science officer of the San Diego Supercomputer Center (SDSC). Altintas is also the director of the WIFIRE Lab, which uses data science to fight wildfires – which she likens to fighting COVID-19.

Rick Stevens is associate lab director for computing, environment and life sciences at Argonne National Laboratory. Stevens has been applying machine learning techniques to drug discovery for COVID-19 in an effort to compress the early stage of drug development, which normally take years to complete.

From left to right: Rommie Amaro; Alessandro “Alex” Vespignani; Ilkay Altintas; and Rick Stevens.

 

HPC rose to the occasion…

HPC, of course, has been crucial to fighting the pandemic. As early as the final months of 2019, computing systems were alerting researchers and policy-makers to the rise of the coronavirus; over the following year, the world’s supercomputers and cloud systems moved with common purpose to understand SARS-CoV-2, stem its spread and quickly develop therapeutics and vaccines to fight its progression in the human body.

SARS-CoV-2’s spike protein without (left) and with (right) its protective glycan shield. Image courtesy of Rommie Amaro.

The panelists spoke to their personal experiences with this fight. Amaro’s all-atom model, for instance, will help identify crucial drug targets on the virus’ spike protein by modeling its glycan shield; Vespignani has been working to model the spread of COVID-19 using commuter network data; Altintas launched the TemPredict project, which is using wearable health monitors to create an early alert system; and Stevens’ machine learning approach has identified 40 promising molecules that are currently undergoing further experimental analysis.

… but experimental bottlenecks stood in the way.

“The rate-limiter step right now isn’t our ability to train machine learning models,” Stevens said. “It’s really the experimental process at the other end. We’re able to make a lot of predictions much faster than we can assay them, and certainly much faster than we can get compounds.”

The other panelists agreed. Offering a “sobering perspective,” Vespignani lamented delays in data reporting and generally low granularity that had limited the efficacy of high-performance approaches to data analysis. “It’s really the real-world data that is holding us back,” he said.

“There really are a lot of challenges,” Amaro added, saying that “good structural starting data points” were necessary, and that data collection processes and workflows could be better optimized.

Stevens went a step further: automated data acquisition; automated experiments; automated chemical synthesis – and more. “Alex [Vespignani] talks about delays in reporting data – well, why the hell aren’t we having mechanisms that can collect this data automatically?” he exclaimed. “Why do people have to be in that loop?”


“… why the hell aren’t we having mechanisms that can collect this data automatically?”


“I think it’s important to recognize that there are many ways we can collect data today,” Altintas said, citing solutions ranging from social media analysis to sensors embedded in infrastructure, like sewage monitoring systems that can detect SARS-CoV-2. “I think the solution to data collection will come from integrating different streams of data into a knowledge environment that many types of questions can be informed with. … It all scales from the atom to the person to the societal level.”

Worries – and hopes – remain for the future

Even with this clear vision of the future in mind, the panelists worried about whether or not it could be realized in time for the next global crisis.

“One of the things that sort of does keep me up at night is: how do we help to make these sort of cultural swings?” Amaro said. “Is it with these sort of leading-edge examples? … Is there another way that we help to catalyze the social construct change?”

The panelists offered their ideas of the roadblocks standing in the way of these transformative changes. Ilkay said that some of it was legal, with impediments stemming from the challenges and responsibilities that come with data handling. Stevens mused on whether it would be better to work outside the healthcare system (particularly in the U.S.) to avoid trudging through the bureaucracy of health data management. Amaro cited the resistance she had experienced from the federal government on coordinating small molecule discovery on a national level, and expressed hope that such an effort might be revisited under another administration.

Some of the panelists also expressed concern that the wartime lessons of COVID-19 would not be retained by a peacetime world: would the infrastructure built during COVID-19 be dismantled after some years without another pandemic? Would governments invest in the additional policies, training and infrastructure necessary to respond quickly to the next health crisis?


“This is our preparation for SARS 3.”


“This is our preparation for SARS 3,” Amaro said. “This is our preparation for when we lose antibiotics, this is our preparation for when it’s so hot that everything starts to die. We’re going to have to adjust to working in super-high-stress, super-integrated environments.”

“We’re gonna have this crisis of domain expertise,” Stevens said. “We’re gonna get lots and lots of datasets, and we’ll have CS people, and architectures that can do AI, but we’re gonna have this rate-limiting step, which is gonna be … actually understanding anything.”

While the future remains disquietingly unclear, the aspiration couldn’t have been clearer.

“We have to push into the experimental space to build a balanced ecosystem where the simulation, the AI and the experiments are gonna come along at kind of the same rate,” Stevens insisted. “It’s the business, of course, of SC to dream these things.”

Subscribe to HPCwire's Weekly Update!

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

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire