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, and computer science to take maximum advantage of high-performance computing resources.
The Funding Opportunity Announcement, sponsored by the High Energy Physics and Advanced Scientific Computing Research program offices within the Department’s Office of Science, can be found here. Applications are open to DOE National Laboratories for multi-institutional, multi-disciplinary, consortium proposals. Lead laboratories are encouraged to engage universities and to support DOE SC diversity, equity, and inclusion guidelines.
Total planned funding is up to $30 million, with $6 million anticipated in Fiscal Year 2022 dollars and outyear funding contingent on congressional appropriations.
This is the fifth round of the SciDAC Partnership in High Energy Physics (HEP), which focuses on computing for high energy physics experiments, theory, and related technology to understand the universe. Scientists anticipate a ten-fold increase in data and complexity in HEP experiments at the Large Hadron Collider in the next few years as well as large increases in the computing needs for neutrino experiments and cosmic surveys. Effective use of DOE’s high-performance computing resources is necessary to tackle these challenges, and the SciDAC partnerships are expected to play a key role.
“This partnership accelerates our progress toward making discoveries about the universe by building collaborations between particle physicists and the teams of experts we need to take full advantage of DOE’s supercomputers,” said Jim Siegrist, Associate Director of Science for High Energy Physics. “Previous SciDAC collaborations have developed computational solutions to significant challenges in high energy physics and enabled high-fidelity simulations of particle processes.”
