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Lavanya Gonzala3

Berkeley Lab Projects Advance Running, Scheduling of Scientific Workflows on HPC Systems

December 4, 2017

Researchers are increasingly turning to high performance computing (HPC) systems to carry out scientific workflows, which are executed as a series of steps and programs to study complex problems. However, achieving this can require a number of time-consuming manual tasks by the user and doesn’t always make the most efficient use of the system. Recently, researchers at the Department of Energy’s (DOE) Lawrence Berkeley National Laboratory (Berkeley Lab) released publicly available software… Read More »


Berkeley Lab Staff to Participate in Major Machine Learning Conference

December 1, 2017

Berkeley Lab’s growing involvement in deep learning research and development will be evident next week when several staff members present papers and posters for the first time at the 2017 Conference on Neural Information Processing Systems. Read More »


CS Staff Honored with Director's Awards for Service and Outreach

December 1, 2017

Jon Bashor, Daniela Ushizima and Mariam Kiran were honored at the Berkeley Lab Director’s Awards for Exceptional Achievement ceremony on November 30. Read More »

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High-Performance Computing Cuts Particle Collision Data Prep Time

November 28, 2017

A new approach to raw data reconstruction has potential to turn particle tracks into physics discoveries faster. And, Brookhaven National Laboratory researchers recently proved the concept with help from NERSC supercomputers & ESnet's high-speed network. Read More »


NERSC Resources Help Predict New Material for High-Power, High-Efficiency LEDs

November 22, 2017

Using predictive atomistic calculations and high-performance supercomputers at NERSC, University of Michigan researchers found that incorporating the element boron into the widely used InGaN (indium-gallium nitride) material can keep electrons from becoming too crowded in LEDs, making the material more efficient at producing light. Read More »


GraphBLAS: Building Blocks For High Performance Graph Analytics

November 21, 2017

After nearly five years of collaboration between researchers in academia, industry and national research laboratories—including Berkeley Lab's Aydın Buluç—GraphBLAS, a collection of standardized building blocks for graph algorithms in the language of linear algebra, is publicly available. Read More »


Deep Learning for Science: A Q&A with NERSC's Prabhat

November 10, 2017

In this Q&A with Prabhat, who leads the Data and Analytics Services Group at NERSC and has been instrumental in several projects exploring opportunities for deep learning in science, he talks about the history of deep learning and machine learning and the unique challenges of applying these data analytics tools to science. Read More »

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The Mystery of the Star That Wouldn’t Die

November 8, 2017

Berkeley Lab and UC Berkeley scientists were part of a team that helped to decipher one of the most bizarre spectacles ever seen in the night sky: A supernova that refused to stop shining, remaining bright far longer than an ordinary stellar explosion. What caused the event is puzzling. Read More »

Corcoran Zamora2

Students Turn Summer Research into SC17 Research Poster

November 7, 2017

Instead of going on vacation last summer, recent computer science graduates Tom Corcoran and Rafael Zamora went to work at Lawrence Berkeley National Laboratory. They were invited to stay on at the lab because of their advanced work at the intersection of protein classification and machine learning. Their project also got them an invitation to present their work at the 2017 Supercomputing Conference in Denver. At the conference, to be held November 12-17, the two will present a poster… Read More »

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Berkeley Lab’s Leadership in Deep Learning, Exascale Computing and Beyond on Tap at SC17

November 6, 2017

Lawrence Berkeley National Laboratory staff will be sharing their expertise reflecting the lab’s work in pushing the envelope to exascale computing and beyond, as well as Berkeley Lab’s leadership in deep learning. Read More »