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Berkeley Researchers Use Machine Learning to Search Science Data

June 19, 2018

Science Search, a web-based search engine for scientific data is currently being developed by a team of researchers in Berkeley Lab's CRD and NERSC. The team is also developing innovative machine learning tools to pull contextual information from scientific datasets and automatically generate missing metadata tags for each file. As a proof-of-concept, the team is working with staff at the Molecular Foundry, to demonstrate the concepts of Science Search on the images captured by the facility's instruments. Read More »

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Self-Healing Cement Could Be a Boon to Oil & Gas Industry

May 24, 2018

Researchers at Pacific Northwest National Laboratory have developed a unique cement that can repair itself in as little as a few hours; simulations run at NERSC helped them understand how it works. Read More »

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Quarterbacking Catalysts by Positioning Atoms

April 18, 2018

Materials science researchers at Pacific Northwest National Laboratory used experiments involving graphene, along with calculations run at NERSC, to better understand how oxygen atoms bind with graphene and turn graphene into a unique catalytic support. Read More »

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Tiny Distortions Reveal Clearer Picture of Strands in Cosmic Web

April 10, 2018

Scientists have decoded faint distortions in the patterns of the universe’s earliest light to map huge tubelike structures invisible to our eyes – known as filaments – that serve as superhighways for delivering matter to dense hubs such as galaxy clusters. Read More »

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Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 29, 2018

Petaflop per second deep learning training performance on the Cori supercomputer at NERSC has given climate scientists the ability to use machine learning to identify extreme weather events in huge climate simulation datasets. Read More »

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Underground Neutrino Experiment Could Provide Greater Clarity on Matter-Antimatter Imbalance

March 26, 2018

A new underground neutrino experiment could provide greater clarity on matter-antimatter imbalance in the Cosmos. And NERSC will be the principal site for data processing and analyses throughout the course of the experiment. Read More »

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NERSC Supercomputers Help Researchers Create Reference Catalog for Rumen Microbiome

March 19, 2018

Using supercomputers at NERSC, an international team led by William Kelly, formerly at AgResearch New Zealand’s Grasslands Research Centre, and including scientists at the Joint Genome Institute generated a reference catalog of rumen microbial genomes and isolates cultivated and sequenced from the Hungate1000 collection. Read More »

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A Game Changer: Metagenomic Clustering Powered by HPC

March 12, 2018

A team of researchers from Berkeley Lab's CRD and JGI took one of the most popular clustering approaches in modern biology—the Markov Clustering algorithm—and modified it to run quickly, efficiently and at scale on distributed-memory supercomputers. Read More »

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Can Strongly Lensed Type Ia Supernovae Resolve One of Cosmology’s Biggest Controversies?

March 1, 2018

Using the SciDAC developed SEDONA code and NERSC supercomputers, astrophysicists at Berkeley Lab and the University of Portsmouth discovered how to control the effects of "micolensing." Armed with this knowledge they believe they will be able to find 1000 strongly lensed Type Ia supernovae in real-time from LSST data--that's 20 times more than previous expectations. Read More »

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The Atomic Dynamics of Rare Magneto-Electric Matter

February 14, 2018

By ricocheting neutrons off the atoms of yttrium manganite (YMnO3) heated to 3,000 degrees Fahrenheit, researchers have discovered the atomic mechanisms that give the unusual material its rare electromagnetic properties. Their work included quantum simulations run at NERSC. Read More »

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Physics Data Processing at NERSC Dramatically Cuts Reconstruction Time

February 6, 2018

In a recent demonstration project, physicists from Brookhaven National Laboratory and Berkeley Lab used the Cori supercomputer to reconstruct data collected from a nuclear physics experiment, an advance that could dramatically reduce the time it takes to make detailed data available for scientific discoveries. Read More »

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Delivering Efficient Parallel I/O with HDF5 on Exascale Computing Systems

February 1, 2018

In an interview with Department of Energy's ECP communications team, Berkeley Lab's Suren Byna and Quincey Koziol talk about delivering efficient parallel I/O with HDF5 on exascale computing systems. Read More »

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Berkeley Lab Physicists Apply Machine Learning to the Universe’s Mysteries

January 30, 2018

Berkeley Lab physicists and their collaborators have demonstrated that computers are ready to tackle the universe’s greatest mysteries – they used neural networks to perform a deep dive into data simulating the subatomic particle soup that may have existed just microseconds after the big bang. Read More »

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Charting a New Course in Organic Solar Cell Design

January 24, 2018

Scientists have pinpointed the source of an ultrafast and efficient process that spawns several carriers of electrical charge from a single particle of light in organic crystals that are integral to this increasingly popular form of solar cells. Read More »

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Coupling Experiments to Theory to Build a Better Battery

January 18, 2018

A research team led by Berkeley Lab found that a new lithium-sulfur battery component allows a doubling in capacity compared to a conventional lithium-sulfur battery. Read More »

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The Blob that Ate the Tokamak

January 11, 2018

Scientists at Princeton Plasma Physics Laboratory used NERSC resources to create new simulations that could provide insight into how blobs (bubbles) at the plasma edge in a tokamak reactor behave. Read More »