News
CRD Summer Students, Advisor Use Virtual Visits to Conduct Real Research
Although Computing Sciences canceled on-site student research projects, many of the students accepted for the summer were able to gain valuable research experience and knowledge. Read More »
CS Postdoc Wins Berkeley Lab SLAM
What starts out 10 times the size of our sun, runs out of fuel, and collapses into a dense object about the size of Berkeley? Answering that question landed postdoc Revathi Jambunathan of the Center for Computational Sciences and Engineering first place in the annual Berkeley Lab SLAM held Thursday, Sept. 17. Read More »
ESnet Summer Students Make the Most of Their Remote Internships
Like many organizations adjusting to a changing work environment amid the COVID-19 pandemic, all of ESnet’s summer students did their internships remotely this year. As their internships draw to a close, we talked with a few of our students about their experiences. Read More »
NERSC Summer Students Take Deep Learning to the Next Level
NERSC summer students this year focused on applying deep learning methods to an array of science applications, from weather and climate modeling to improving I/O scaling for GPUs. Read More »
Berkeley Lab’s ENDURABLE: An Aggregate Data Standard for AI Modeling
DOE announced $8.5 million for projects to make artificial intelligence models and data more accessible and reusable. One of these newly funded projects is “ENDURABLE: Benchmark datasets for AI with queryable metadata,” spearheaded by Berkeley Lab’s Computational Research Division. Read More »
New $115 Million Quantum Systems Accelerator to Pioneer Quantum Technologies for Discovery Science
The Department of Energy has awarded $115 million over five years to the Quantum Systems Accelerator (QSA), a new research center led by Berkeley Lab that will forge the technological solutions needed to harness quantum information science for discoveries that benefit the world Read More »
Physical Scientists Turn to Deep Learning to Improve Earth Systems Modeling
Weather, climate, and Earth systems modeling are emerging as an exciting application area for physics-informed deep learning that can more effectively identify nonlinear relationships in large datasets, extract patterns, emulate complex physical processes, and build predictive models. Read More »
Searching for Evidence of a ‘Neutrinoless’ Particle Process
Nuclear physicists affiliated with Berkeley Lab played a leading role in analyzing data at NERSC for CUPID-Mo, a demonstration experiment that has achieved record precision for a specialized detector material. Read More »
Berkeley Lab staff hold leadership roles in SciDAC Institutes
Over the next five years, the U.S. Department of Energy will provide $57.5 million for two Scientific Discovery through Advanced Computing Institutes. And Berkeley Lab staff will continue to hold leadership positions in both—Esmond Ng as director of FASTMath and Lenny Oliker as deputy director of RAPIDS2. Read More »
Graph Neural Networks Open New Doors in Particle Physics Research
High-performance data analysis tools are helping the HEP research community find more efficient ways to sift through, reconstruct, and analyze the increasing amounts of detector data available to them. Read More »