AI for Science Town Hall Series Kicks off at Argonne

By Tiffany Trader

August 2, 2019

Last week (July 22-23), Argonne National Lab, future home to the Intel-Cray Aurora supercomputer, hosted the first in a series of four AI for Science town hall meetings being convened by Department of Energy laboratories. The meetings are aimed at soliciting and collecting “community input on the opportunities and challenges facing the scientific community in the era of convergence of high-performance computing and artificial intelligence (AI) technologies.”

In alignment with DOE missions and the U.S. national AI initiative, the DOE community and their collaborators are being engaged to discuss broadly the opportunities that can be realized by advancing and accelerating the development of AI capabilities for science and science use cases.

Rick Stevens

“We’re asking the fundamental question: what do we have to do in the AI space to make it relevant for science? The point of the town halls is to get people thinking about what opportunities there are in different scientific domains for breakthrough science that can be accomplished by leveraging AI and working AI into simulation, bringing AI into big data, bringing AI to the facility and so forth,” said Argonne’s Rick Stevens in an interview with HPCwire. Stevens is co-chairing the town hall program along with Berkeley Lab’s Kathy Yelick and Oak Ridge Lab’s Jeff Nichols.

Each of the four town halls (held at Argonne, Oak Ridge, Berkeley, and in Washington, DC) encompasses high-level talks, application tracks and cross-cutting breakout sessions. The two-day Argonne event drew about 350 people, DOE and university researchers, primarily from the Midwest region, with about 150 people coming from other parts of the country (including broad lab participation).

The first day focused on application breakouts by science domain (e.g., chemistry, mathematics, materials, climate, biology, high energy physics, nuclear physics); on day two, participants were reoriented to cross-cutting topics, spanning fundamental math issues, software issues, data issues, understandability issues, uncertainty quantification, facilities, integration of simulation and AI, computer architecture directions, among others.

The town halls will result in an integrated report to be published by the end of the year, which will inform strategic planning, and help shape programs and budgets.

If the town hall format sounds familiar, you may recall that a series of exascale town halls was held in 2007, helping sow the seeds for the US Department of Energy’s Exascale Computing Initiative (ECI) and Exascale Computing Project (ECP). Together these activities, with a focus on codesign, application readiness and “capable exascale,” are preparing the U.S. to stand up multiple exascale-class systems in the 2021-2023 timeframe.

Learnings from the AI town halls could conceivably lead to a more targeted, and potentially funded, policy not unlike how the exascale town halls helped establish a robust national exascale program.

“We’ve got this huge exascale program and we’re now asking the question, what’s the opportunity for AI in the science space, particularly in the context of DOE but also more broadly with NIH and other agencies,” said Stevens, Argonne’s associate laboratory director for computing, environment and life sciences.

Maintaining leadership in AI is the primary directive of the U.S. national AI initiative, launched by the White House in February. The announcement and subsequent OMB budget priority letters that went out to the agencies declared progress in AI as the number one priority across the agencies.

That AI initiative also challenged agencies to come up with plans, to determine resource levels, and make progress on managing their data. It laid out a very high level blueprint as to what the country needs to do maintain progress in AI and to complement in the academic and government sector what’s going on at the internet companies, Stevens told HPCwire.

The Chicago AI for Science Town Hall at Argonne National Laboratory

“Clearly there’s huge progress in the internet space, but those Facebooks and Googles and Microsofts and Amazons and so on, those guys are not going to be the primary drivers for AI in areas like high-energy physics or nuclear energy or wind power or new materials for solar or for cancer research – it’s not their business focus,” Stevens maintained. “We recognize that the challenge is how to leverage the investments made by the private sector to build on those [advances] to add what’s missing for scientific applications — and there’s lots of things missing. And then figure out what the computing community has to do to position the infrastructure and our investments in software and algorithms and math and so on to bring the AI opportunity closer to where we currently are.”

The overarching agenda for the AI for Science town hall program includes a set of “charge questions” aimed at surfacing the most compelling problems where AI could have an impact and identifying the requirements at the research and facility level needed to realize these opportunities.

We posed one of these questions to Stevens: What are 3-5 open questions that need to be addressed to maximally contribute to AI impact in the science domains and AI impact in the enabling technologies?

His top three:

+ Uncertainty quantification, i.e. model confidence — “When you’re doing cat videos, no one cares what your confidence interval is, where your error bars are exactly, but in a scientific, a medical application, you need to know that the answer is likely to be correct.”

+ The direction of AI architectures – “Are the architectures that are being developed to accelerate general AI research – are they in fact even what we need for the types of data and the types of networks and systems we need to build for applying AI in science?”

+ Injecting AI with ground truth – “Our first way of thinking about the world is in some sense, do we have a mechanistic model of it, a physical model to simulate? And most of the progress in AI involves non-physical modeling. If you think about natural language processing, there’s no physical model for that. If you think about computer vision, most of the kinds of things that people do with computer vision, there’s no physical model; there is no ground truth that you can generate from first principles. But in many scientific areas, we’ve had 400 years of progress, in physics and chemistry and biology and so forth, and we have a lot of physical understanding. How do we use that physical understanding combined with data to build AI models that actually internalize that physical understanding? In other words, having these models be able to make predictions in the world as opposed to in some abstract space.”

The AI for Science Town Hall series continues at Oak Ridge National Laboratory (Aug. 20-21, 2019), Lawrence Berkeley National Laboratory (Sept. 11-12, 2019) and Washington DC (Oct. 22-23, 2019).

Link for more info: https://web.cvent.com/event/b03cf98d-d350-4f66-805a-1a19f03bdcf8/summary

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!

Red Hat’s Disruption of CentOS Unleashes Storm of Dissent

January 22, 2021

Five weeks after angering much of the CentOS Linux developer community by unveiling controversial changes to the no-cost CentOS operating system, Red Hat has unveiled alternatives for affected users that give them severa Read more…

By Todd R. Weiss

China Unveils First 7nm Chip: Big Island

January 22, 2021

Shanghai Tianshu Zhaoxin Semiconductor Co. is claiming China’s first 7-nanometer chip, described as a leading-edge, general-purpose cloud computing chip based on a proprietary GPU architecture. Dubbed “Big Island Read more…

By George Leopold

HiPEAC Keynote: In-Memory Computing Steps Closer to Practical Reality

January 21, 2021

Pursuit of in-memory computing has long been an active area with recent progress showing promise. Just how in-memory computing works, how close it is to practical application, and what are some of the key opportunities a Read more…

By John Russell

HiPEAC’s Vision for a New Cyber Era, a ‘Continuum of Computing’

January 21, 2021

Earlier this week (Jan. 19), HiPEAC — the European Network on High Performance and Embedded Architecture and Compilation — published the 8th edition of the HiPEAC Vision, detailing an increasingly interconnected computing landscape where complex tasks are carried out across multiple... Read more…

By Tiffany Trader

Supercomputers Assist Hunt for Mysterious Axion Particle

January 21, 2021

In the 1970s, scientists theorized the existence of axions: particles born in the hearts of stars that, when exposed to a magnetic field, become light particles, and which may even comprise dark matter. To date, however, Read more…

By Oliver Peckham

AWS Solution Channel

Fire Dynamics Simulation CFD workflow on AWS

Modeling fires is key for many industries, from the design of new buildings, defining evacuation procedures for trains, planes and ships, and even the spread of wildfires. 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…

Researchers Train Fluid Dynamics Neural Networks on Supercomputers

January 21, 2021

Fluid dynamics simulations are critical for applications ranging from wind turbine design to aircraft optimization. Running these simulations through direct numerical simulations, however, is computationally costly. Many Read more…

By Oliver Peckham

Red Hat’s Disruption of CentOS Unleashes Storm of Dissent

January 22, 2021

Five weeks after angering much of the CentOS Linux developer community by unveiling controversial changes to the no-cost CentOS operating system, Red Hat has un Read more…

By Todd R. Weiss

HiPEAC Keynote: In-Memory Computing Steps Closer to Practical Reality

January 21, 2021

Pursuit of in-memory computing has long been an active area with recent progress showing promise. Just how in-memory computing works, how close it is to practic Read more…

By John Russell

HiPEAC’s Vision for a New Cyber Era, a ‘Continuum of Computing’

January 21, 2021

Earlier this week (Jan. 19), HiPEAC — the European Network on High Performance and Embedded Architecture and Compilation — published the 8th edition of the HiPEAC Vision, detailing an increasingly interconnected computing landscape where complex tasks are carried out across multiple... Read more…

By Tiffany Trader

Saudi Aramco Unveils Dammam 7, Its New Top Ten Supercomputer

January 21, 2021

By revenue, oil and gas giant Saudi Aramco is one of the largest companies in the world, and it has historically employed commensurate amounts of supercomputing Read more…

By Oliver Peckham

President-elect Biden Taps Eric Lander and Deep Team on Science Policy

January 19, 2021

Last Friday U.S. President-elect Joe Biden named The Broad Institute founding director and president Eric Lander as his science advisor and as director of the Office of Science and Technology Policy. Lander, 63, is a mathematician by training and distinguished life sciences... Read more…

By John Russell

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

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

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

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

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

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

Leading Solution Providers

Contributors

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

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

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 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

Intel Xe-HP GPU Deployed for Aurora Exascale Development

November 17, 2020

At SC20, Intel announced that it is making its Xe-HP high performance discrete GPUs available to early access developers. Notably, the new chips have been deplo Read more…

By Tiffany Trader

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

HPE, AMD and EuroHPC Partner for Pre-Exascale LUMI Supercomputer

October 21, 2020

Not even a week after Nvidia announced that it would be providing hardware for the first four of the eight planned EuroHPC systems, HPE and AMD are announcing a Read more…

By Oliver Peckham

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