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M-TIP Extracts Biological Structure from Limited Data

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A new Berkeley Lab algorithmic framework called multi-tiered iterative phasing (M-TIP) utilizes advanced mathematical techniques to determine 3D molecular structure of important nanoobjects like proteins and viruses from very sparse sets of noisy, single-particle data. » Read More

Using Brain-Inspired Chips to Tackle Science's Big Data

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Although neuromorphic computing is still in its infancy, researchers in Berkeley Lab's CRD hope that these tiny, low-power, brain-inspired computing systems could one day help alleviate some of science’s big data challenges. » Read More

45 Qubit Simulation Optimized Using Roofline Model

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Researchers who ran a record 45 qubit simulation worked with NERSC staff and used the CRD Roofline Model to identify potential performance boosts. » Read More

A Math "Shortcut" Opens Opportunities for Chemistry

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A new math “shortcut” developed by CRD's Chao Yang is speeding up molecular absorption calculations by a factor of five, so simulations that used to take 10 to 15 hours to compute can now be done in approximately 2.5 hours. The algorithm will be incorporated in an upcoming release of the widely used NWChem computational chemistry suite. » Read More

HPC4Mfg Paper Manufacturing Project Yields Results

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An HPC for Manufacturing project co-led by CRD's David Trebotich could help U.S. paper manufacturers significantly reduce production costs and increase energy efficiencies.The papermaking industry currently ranks third among the country’s largest energy users, behind only petroleum refining and chemical production. » Read More

News

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New Data Archive Aims to Amplify Impact of Ecosystem Research

July 21, 2017

Berkeley Lab’s Computing Sciences and Earth & Environmental Sciences Area are partnering on a three-year project to develop an archive that will serve as a repository for hundreds of DOE-funded research projects under the agency’s Environmental System Science umbrella.

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New Berkeley Lab Algorithms Extract Biological Structure from Limited Data

July 10, 2017

A new Berkeley Lab algorithmic framework called multi-tiered iterative phasing (M-TIP) utilizes advanced mathematical techniques to determine 3D molecular structure of important nanoobjects like proteins and viruses from very sparse sets of noisy, single-particle data.


LBL TrueNorth v1

Will Brain-Inspired Chips Make a Dent in Science’s Big Data Problems?

July 5, 2017

Although neuromorphic computing is still in its infancy, researchers in Berkeley Lab's CRD hope that these tiny, low-power, brain-inspired computing systems could one day help alleviate some of science’s big data challenges.

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Erich Strohmaier Named ISC 2017 Conference Fellow

June 6, 2017

The ISC High Performance conference (ISC 2017) named Berkeley Lab’s Eric Strohmaier an ISC Fellow. Strohmaier is known internationally for his role as a founding editor of the twice-yearly TOP500 list of the world’s top supercomputers.