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For 20 years, Berkeley Lab’s GASNet has been fueling developers’ ability to tap the power of massively parallel supercomputers more effectively. The middleware was recently upgraded to support exascale scientific applications.
The latest developments in computational oncology are giving medical researchers a glimpse into a future where they’ll be able to understand tumor progression via supercomputers and advanced mathematical algorithms.
Five Computing Sciences Area staff will accept Director’s Awards for Exceptional Achievement in areas ranging from service to scientific achievement at a ceremony to be held November 10. The CS Area award recipients are David Brown, Marcus Noack, Talita Perciano, Silvia Crivelli, and Michael Wehner.
Over the past seven years, the Berkeley Lab-led Exabiome project developed novel software tools that allow researchers to harness the power of cutting-edge high performance computers (and now exascale supercomputers) to solve previously infeasible problems in metagenomics.
Full-scale, biophysically accurate simulations run at NERSC used machine learning and observational data to show which neurons generate the recorded signals.
Berkeley Lab's Advanced Quantum Testbed team demonstrates a three-qubit native quantum gate with high fidelity
The WarpX project has spent the last six years creating a novel, highly parallel, and highly optimized single-source simulation code for modeling plasma-based particle colliders on cutting-edge exascale supercomputers, with broad importance for other accelerators and related problems.
Berkeley Lab’s Daniela Ushizima was recognized with PMWC Pioneer Award for constructing “a new and reliable technique for diagnosing Alzheimer’s disease and measuring the efficacy of experimental treatments.”
A group of Berkeley Lab scientists has developed and tested several machine learning techniques organized in a learning pipeline to improve the interpretation of increasingly large cryo-ET datasets.
Jean Luca Bez, a postdoctoral scholar in the Scientific Data Management Research (SDMR) group was recognized with an Honorable Mention by the Better Scientific Software (BSSw) Fellowship Program.
Bert de Jong has been selected as a 2023 fellow of the Oppenheimer Science and Energy Leadership Program (OSELP).
For 20 years, Berkeley Lab’s GASNet has been fueling developers’ ability to tap the power of massively parallel supercomputers more effectively. The middleware was recently upgraded to support exascale scientific applications.
SciData transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures with scientific partners.
The Applied Mathematics & Computational Research Division conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture, and high-performance software implementation.
The Center for Advanced Mathematics for Energy Research Applications (CAMERA) is an integrated, cross-disciplinary center aimed at inventing, developing, and delivering the fundamental new mathematics required to capitalize on experimental investigations at scientific facilities.
The Quantum Systems Accelerator is catalyzing national leadership in quantum information science to co-design the algorithms, quantum devices, and engineering solutions needed to deliver certified quantum advantage in Department of Energy scientific applications. Berkeley Lab leads the center. Sandia National Laboratories is the lead partner.
