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SC20 Wrap-up: From the Gordon Bell Prize to Machine Learning, Quantum Computing, and More

November 23, 2020

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As they have for nearly three decades, Berkeley Lab Computing Sciences Area staff from the Computational Research Division, ESnet, and NERSC shared their expertise with the global HPC community at SC20 – albeit this year in virtual mode. From tutorials and workshops to papers, posters, panels, and more, it was a busy couple of weeks for all involved.

Here are a few highlights:

Gordon Bell Prize

CRD researchers were part of the team that won the 2020 ACM Gordon Bell Prize for DeePMD-kit, a new machine-learning-based software package that uses neural networks to enhance molecular dynamics modeling. They demonstrated what can be achieved by integrating physics-based modeling and simulation, machine learning, and efficient implementation on a next-generation computational platform.

In addition, researchers from CRD and NERSC were lead authors on a paper that was a finalist for this year’s Gordon Bell Prize. The team demonstrated how advancements to the BerkeleyGW materials science code enables large-scale, excited-state calculations to run in just minutes on HPC systems.

Best Paper Award

“The Performance and Energy Efficiency Potential of FPGAs in Scientific Computing” won the best paper award at the 11th IEEE International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, held in conjunction with SC20. Authors: Tan Nguyen (CRD), Samuel Williams (CRD), Marco Siracusa, Colin MacLean (NERSC), Douglas Doerfler (NERSC), Nicholas Wright (NERSC)

Best Presentation Award

Researchers from Berkeley Lab’s Advanced Light Source, the CAMERA division, and NERSC won the Best Presentation Award at the XLOOP workshop, held in conjunction with SC20, for “Interactive Parallel Workflows for Synchrotron Tomography.” Authors: Dula Parkinson (ALS), Harinarayan Krishnan (CRD), Daniela Ushizima (CRD), Matthew Henderson (CRD), Shreyas Cholia (NERSC)

Best Research Poster Finalist

While interning at NERSC this year, University of Arizona Ph.D. Student Kevin Luna used deep learning to accelerate traditional PDE-based simulations in real time. This work earned him a spot as a finalist in the Best Research Poster competition at SC20.

Best Student Paper Finalist

A paper describing MeshfreeFlowNet — an open-source, physics-constrained, deep-learning approach for enhancing the spatial and temporal resolution of scientific data — was a finalist for the Best Student Paper Award at SC20. The lead author, Max Jiang of UC Berkeley, has been affiliated with NERSC since 2018.

1st International Workshop on Quantum Computing Software

This first-of-its-kind SC20 event explored the innovative software that is needed to make quantum computing practical and accessible. Learn more about the workshop in this Q&A with CRD’s Bert de Jong, who was on the program committee.

Deep Learning Improves High-Performance Networking

ESnet’s Mariam Kiran gave a lightning talk at SC20 on DAPHNE (Deep Learning and Artificial Intelligence for High-Performance Networks), a project she leads that is developing next-generation software tools to help scientists better predict the best time and date to schedule large-scale data transfers across ESnet.

Beyond Moore’s Law: Disaggregated Architectures

CRD’s John Shalf was part of a panel discussion on emerging high performance computing platforms at a webinar on “Disaggregated System Architectures for Next Generation HPC and AI Workloads,” held during SC20.

About Computing Sciences at Berkeley Lab

The Computing Sciences Area at Lawrence Berkeley National Laboratory provides the computing and networking resources and expertise critical to advancing Department of Energy Office of Science research missions: developing new energy sources, improving energy efficiency, developing new materials, and increasing our understanding of ourselves, our world, and our universe.

Founded in 1931 on the belief that the biggest scientific challenges are best addressed by teams, Lawrence Berkeley National Laboratory and its scientists have been recognized with 13 Nobel Prizes. Today, Berkeley Lab researchers develop sustainable energy and environmental solutions, create useful new materials, advance the frontiers of computing, and probe the mysteries of life, matter, and the universe. Scientists from around the world rely on the Lab’s facilities for their own discovery science. Berkeley Lab is a multiprogram national laboratory, managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.