ASF Keynotes Showcase How HPC and Big Data Have Pervaded the Pandemic

By Oliver Peckham

February 24, 2021

Last Thursday, a range of experts joined the Advanced Scale Forum (ASF) in a rapid-fire roundtable to discuss how advanced technologies have transformed the way humanity responded to the COVID-19 pandemic in indelible ways. The roundtable, held near the one-year mark of the first lockdowns in North America, opened with a session from Ari Berman, CEO of BioTeam.

“It’s so easy to focus on the bad things we hear about the remarkable and really unfortunate numbers of people who have died from this, the huge numbers of people who’ve been infected from it, we talk about these new more infectious variants, et cetera,” Berman said – but, he added, there were major success stories in the pandemic, too: collaborations and technology deployments that will save “millions of lives.” (To watch the opening session, click here.)


Dr. Susan Gregurick

NIH Keynote: Creating a Coordinated Data Approach to Help Address COVID-19

With that, the roundtable launched into its first keynote, delivered by the National Institutes of Health’s Susan Gregurick, who serves as associate director for data science and director of the NIH’s Office of Data Science Strategy. 

“We’ve been working for almost a year now to sprint ahead to collect and enhance SARS-CoV-2 data – clinical data, structural data, genomics data – to address the pandemic,” Gregurick said. “The first thing that we tried to do – and we did successfully – was to get different types of at-home, point-of-care clinical testing technologies out into the hands of our citizens.”

This program – called RADx – ranges from preparing for high-throughput COVID-19 testing to engaging underserved populations through community-engaged implementation projects, and it’s one of several data-driven projects run inside the NIH. The NIH has also, for instance, been working on its Collaboration to Assess Risk and Identify Long-Term Outcomes (CARING) for Children with COVID Program. 

Still, the NIH needed to develop a longer reach. They worked with the National COVID Cohort Collaborative (N3C), which integrates electronic healthcare record data on COVID-19, augmenting it with “an incredibly rich set of data from vulnerable populations.” As of a few months ago, the N3C has multiple millions of participants contributing data to hundreds of ongoing projects and collaborators. (The data is accessible in a cloud archive, which is accessible here.) 

The NIH also worked with the All of Us Research program – which collects longitudinal COVID-19 health outcome data alongside phenotypic and serological data – the BioData Catalyst, which provides data from clinical trials and observational studies such as those that evaluated hydroxychloroquine early in the pandemic. 

Soon enough, the NIH found itself serving as an aggregator of a wide range of data from various sources – and having to grapple with the logistical implications of coordinating both the data and access to the data across a wide range of interested parties.

“Making all this work together across many different projects really does require some efforts in data harmonization,” Gregurick said. “We’ve been tackling this in two different ways: … common data elements and mapping to data models. In some cases it’s a development of curation strategies within the data hub, … in other cases it’s at the point of collection and really collaborating with our data coordination centers.” 

The different stages of the RADx program, for instance, shared around 16 common data elements (CDEs) that could be more easily integrated, but each program also contained its own unique elements. “We’re using those common data elements to help construct data models and data search strategies for ontology,” Gregurick said. “We’re also mapping these to a common data model.” 

The NIH has also been working on unifying other supporting technology, such as the researcher authentication services that allow access to various data, tools and hubs, across platforms. More ambitiously, they’re piloting a program to allow the linking of records from a given individual across platforms without compromising that individual’s identity.

Image courtesy of Susan Gregurick.

“We are now looking to create data linkages across many repositories and many studies, building up ways to enhance data discovery across multiple platforms,” Gregurick said, “and ways to pull and aggregate data together into a workbench that allows for greater analysis of the data no matter where the data sits.” 

“Pretty soon we’re gonna start talking about what’s colloquially called ‘long COVID,’” she added. “Many researchers ask questions about long-term morbidity of COVID, and then geographic differences in patient outcomes. Being able to ask those types of questions is really a question of pulling together data from different types of platforms.”

To watch Gregurick’s keynote, click here.


Google Keynote: Harnessing the Scale of Cloud to Accelerate Discovery of COVID-19 Therapeutics

Drs. Haribabu Arthanari, Christoph Gorgulla and William Magro

Elsewhere, a trio of researchers were making their own data. Haribabu Arthanari and Christoph Gorgulla (hailing from Harvard) and William Magro (from Google), the speakers for the second keynote, had been faced with a colossal scale problem.

“As many of you know, SARS-CoV-2 uses an arsenal of weapons, its tiny molecular machines, the viral proteins, to attack, invade and infect our cells,” Arthanari explained. “Each one of these proteins is important for the virus to replicate itself, and thus offers a therapeutic opportunity for us to target.”

However: “On average, it takes about 15 seconds for us to take a small molecule, place it in a protein, and derive the docking score. By this token, if I had to screen about one billion molecules, that would take me about 475 years. That is per target. Now, we need to do this for multiple targets in a matter of days.”

So, along with Gorgulla, he worked to develop a new method entirely: VirtualFlow. Described in the resulting research paper as “a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large libraries of compounds,” VirtualFlow made short work of the 40 target sites on the SARS-CoV-2 virus, each of which was screened against more than a billion compounds.

Image courtesy of the researchers.

“So how is VirtualFlow able to do this in a matter of days?” Gorgulla said. “The key for this is massive parallelization – and for that we need high-performance computing platforms such as Google Cloud.” Indeed, enabled by Elastifile and Slurm for managing files and workloads, the researchers ran VirtualFlow on up to 160,000 CPUs in parallel, supported by Google-provided research credits for Google Cloud access. 

Late last year, Harvard and Google Cloud were awarded HPCwire’s Readers’ Choice Award for Best Use of HPC in the Cloud for this work. To learn more, click here.

To watch this keynote, click here.


Much, much more

Beyond the keynotes, the ASF roundtable featured a fireside chat on storage architectures for research data hosted by Quantum’s Eric Bassier; a case study session detailing Intel’s contributions to the fight against COVID-19; and another case study session focused on reducing COVID-19 transmission with early detection through wastewater monitoring. 

There were also two highlight sessions from solution providers: one from MemVerge discussing big memory acceleration of single-cell RNA sequencing and another from Panasas discussing optimization of storage performance and capacity for research applications.

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!

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. 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. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named 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…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech 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…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y 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…

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…

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…

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

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…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N 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…

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…

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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire