February 20, 2018: Mathematicians at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new approach to machine learning aimed at experimental imaging data. Rather than relying on the tens… Read More »
- Exascale and Beyond We're rethinking every aspect of scientific computing—hardware, software, algorithms, efficiency and networking—to address limits on processor speed, memory and energy consumption. The goal: more science per Watt.
- Data-Driven Science We develop tools and technologies and provide the critical networking and computer resources that help scientists turn enormous, widely shared, and complex data sets into discoveries.
- Scientific Complexity Engaging scientists in a holistic, team-based approach—from theory, observations and experiments to simulation and data analysis—is a grand challenge and goal of Computing Sciences at Berkeley Lab.
February 15, 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 »
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 large-scale quantum simulations run at NERSC. Read More »