June 18, 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 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 »
- Exascale and Beyond Escalating computing power has enabled science problems inconceivable a few years ago. Continuing this growth requires new devices, architecture and algorithms, software and computing facility operations.
- Quantum Information Sciences Researchers at Berkeley Lab are exploring a drastically different kind of computing architecture based on quantum mechanics to solve some of science’s hardest problems.
- Data-Driven Science The “superfacility” is our vision to help researchers turn the rising tide of experimental and observational data into science by coupling instruments to advanced computing through powerful networks and research expertise.
- Scientific Complexity To answer, and anticipate, increasingly sophisticated science questions, researchers need advanced math models and methods, new algorithms and better ways to use computing and networking.
June 15, 2018: Applied mathematician Mike MacNeil joined the Computational Research Division’s Analytics and Visualization group as a postdoctoral researcher in August 2017, where he is developing new methods and software tools for helping scientists improve their understanding of voluminous and complex, time-varying 3D image-based data acquired by experiments run at Berkeley Lab’s Advanced Light Source. Read More »
June 11, 2018: Machine learning experts, computer scientists and physicists have partnered with Kaggle on the TrackML Particle Tracking Challenge, a competition designed to inspire the development of an algorithm that can quickly reconstruct particle tracks from 3D coordinates left in silicon particle detectors following millions of particle collisions. Read More »