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First Monterey Data Conference does Deep Dive into Deep Learning for Science

August 13, 2019

Kathy Yelick MDC10

Berkeley Lab Computing Sciences Associate Lab Director Kathy Yelick gave an invited talk on machine learning for science during the 2019 Monterey Data Conference.

The Computing Sciences Area (CSA) at Lawrence Berkeley National Laboratory joined forces with the Association for High Speed Computing (AHSC) to organize and support the inaugural Monterey Data Conference, held August 5-8 in Monterey, Calif. This annual, invitation-only meeting was launched this year to give researchers from DOE national laboratories, facilities, universities, and industry the opportunity to share and showcase the latest advances and challenges in scientific data analysis and computing.

The theme for this year’s event was Deep Learning for Science. The program featured talks from leading scientists from across the country who showed the impact of deep learning on a broad set of applications, including precision agriculture, personalized cancer treatment, materials by design, detecting extreme climate events, controlling fusion reactors, managing networks, and tracking particles in advanced physics experiments. The examples went beyond data analysis problems into design and control of experiments and the derivation and refinement of physical models from data, showing how the scientific process and our understanding are being impacted by these methods. Panel discussions from industry and the DOE Labs explored some of the hardware, software, and methods challenges. 

“Over the past several years, there have been rapid innovations in deep learning that promise to transform many scientific disciplines and enable new kinds of scientific discovery,” said Sudip Dosanjh, director of Berkeley Lab's National Energy Research Scientific Computing Center (NERSC). “Even so, challenges remain before we will be able to fully realize deep learning solutions in scientific workflows. Our goal is to facilitate this process by creating and supporting interactive opportunities such as the Monterey Data Conference.”

The conference was organized by a CSA team that included NERSC’s Steve Farrell (who led the team), Dosanjh, Prabhat, Katie Antypas, and Becci Totzke; the Computational Research Division’s Talita Perciano, John Shalf, and Esmond Ng; ESnet’s Mariam Kiran; and AHSC’s Dee Cadena.


About Computing Sciences at Berkeley Lab

The Computing Sciences Area at Lawrence Berkeley National Laboratory(Berkeley Lab) provides the computing and networking resources and expertise critical to advancing Department of Energy Office of Science (DOE-SC) research missions: developing new energy sources, improving energy efficiency, developing new materials, and increasing our understanding of ourselves, our world, and our universe. ESnet, the Energy Sciences Network, provides the high-bandwidth, reliable connections that link scientists at 40 DOE research sites to each other and to experimental facilities and supercomputing centers around the country. The National Energy Research Scientific Computing Center (NERSC) powers the discoveries of 7,000-plus scientists at national laboratories and universities. NERSC and ESnet are both Department of Energy Office of Science National User Facilities. The Computational Research Division (CRD) conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture and high-performance software implementation.

Berkeley Lab addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the DOE’s Office of Science. The DOE Office of Science is the United States' single largest supporter of basic research in the physical sciences and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.