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DOE: $9.25M for Research through Advanced Computing (SciDAC) Partnership in Nuclear Energy

The U.S. Department of Energy (DOE) has announced $9.25 million for research in the behavior and properties of structural materials under molten salt reactor conditions, via collaborations that enable effective use of DOE’s high performance computers. Scientific Discovery through Advanced Computing (SciDAC) brings together experts in key areas of science and energy research with experts […]

DOE: Applications Open for $70M for Scientific Discovery through Advanced Computing (SciDAC)

Nov. 23, 2021 — Today, the U.S. Department of Energy (DOE) announced plans to provide $70 million for research in earth system model development, which will contribute to further development of the Energy Exascale Earth System Model (E3SM) through collaborations  that will use DOE high performance computers (HPC) to enable advanced modeling via mathematical and computational solutions. […]

SciDAC: DOE Funding $30M Opportunity Using HPC for High Energy Physics Research

Today, the U.S. Department of Energy (DOE) announced $30 million for research in computation and simulation techniques and tools “to understand the universe via collaborations that enable effective use of DOE high performance computers.” Scientific Discovery through Advanced Computing (SciDAC) brings together researchers in areas of science and energy with experts in software development, applied mathematics, […]

DOE Funds $28M for Scientific Supercomputing Research Projects

The U.S. Department of Energy (DOE) today announced $28 million in funding for five research projects to develop software designed to better leverage DOE supercomputers in fields such as quantum information science and chemical reactions for clean energy applications. A list of projects can be found here. The projects are sponsored by the Offices of Advanced Scientific Computing […]

SUPER Project Aims at Efficient Supercomputing for Scientists

“SUPER builds on past successes and now includes research into performance auto-tuning, energy efficiency, resilience, multi-objective optimization, and end-to-end tool integration. Leading the project dovetails neatly with Oliker’s research interests, which include optimization of scientific methods on emerging multi-core systems, ultra-efficient designs of domain-optimized computational platforms and performance evaluation of extreme-scale applications on leading supercomputers.”