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At Biden Summit, CRD's Ushizima Discusses Using Machine Learning to Improve Cancer Detection

September 22, 2018

Dani Ushizima, a staff scientist in the Computational Research Division who has adapted algorithms used in materials research to scan for cervical cancer, described her research in a panel discussion at the Sept. 21 East Bay Biden Cancer Community Summit. Read More »

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Berkeley Lab Researchers Co-Author IARIA’s Best Paper

September 21, 2018

A paper co-authored by Berkeley Lab’s Esmond Ng and Chao Yang won best paper at this year’s International Academy, Research, and Industry Association’s (IARIA’s) Computation Tools 2018 conference in Barcelona, Spain. The paper, Deep Learning: A Tool for Computational Nuclear Physics, describes how feed-forward artificial neural networks can be used to predict the properties of atomic nuclei. “Nuclei are complicated quantum many-body systems, and their inter-nucleon interactions are… Read More »

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NERSC-led Team Named 2018 Gordon Bell Prize Finalist for Deep Learning Achievement

September 20, 2018

A team from Berkeley Lab, Oak Ridge National Laboratory and NVIDIA has, for the first time, demonstrated an exascale-class deep learning application that has broken the exaop barrier. Read More »

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NERSC Recognized by NASA for Contributions to Planck Mission

September 17, 2018

A pioneering agreement between the DOE and NASA guaranteed that NERSC would provide the HPC support essential to the Planck mission's success. And for that support, NERSC was recently recognized with a NASA Group Achievement Award. Read More »

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NERSC, Intel, Cray Harness the Power of Deep Learning to Better Understand the Universe

September 5, 2018

A Big Data Center collaboration between computational scientists at NERSC and engineers at Intel and Cray has yielded another first in the quest to apply deep learning to data-intensive science: CosmoFlow, the first large-scale science application to use the TensorFlow framework on a CPU-based high performance computing platform with synchronous training. Read More »

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Old School + New School: Geometry, Physics & Machine Learning Take on Climate Research Data Challenges

September 4, 2018

Two PhD students who first came to Berkeley Lab as summer interns in 2016 are spending six months a year at the lab through 2020 developing new data analytics tools that could dramatically impact climate research and other large-scale science data projects. Read More »

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Berkeley Lab, BIDS Take on Big Data

August 30, 2018

The BIDS ecosystem comprises an impressive network of Fellows, including some who are Berkeley Lab scientists. This month, several Berkeley Lab-BIDS Fellows are organizing two of events to share their data-science expertise: Machine Learning for Science (ML4Sci) Workshop and the California Water Data Hackathon. Read More »

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Exascale Computing Project Spotlights ExaGraph and STRUMPACK/SuperLU Collaboration

August 27, 2018

Results from a collaboration between the Exascale Computing Project's Sparse Solvers Software Technology project and ExaGraph Co-Design Center showed that the parallel AWPM (approximate-weight perfect matching) code can run up to 2,500x faster than the sequential algorithm on 256 nodes of NERSC's Cori supercomputer. Read More »

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Berkeley Lab Researchers Showcase Deep Learning for High Energy Physics at CHEP Conference

August 17, 2018

Steve Farrell, a machine-learning engineer who recently joined NERSC, gave an overview of Berkeley Lab’s expanding expertise in deep learning for science during a plenary talk at the 2018 CHEP conference in July. Read More »

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High School Summer Student is 'Posit-ive' About Coding

August 17, 2018

Sanjana Shah, a high school student from the Peninsula discovered her passion for programming when she attended a coding workshop for youth sponsored by a local tech company. She is also the first (and so far, the only) high school student CRD's David Donofrio has ever hired through the Computing Sciences Summer Student program. Read More »