The US Department of Energy's (DOE's) Scientific Discovery Through Advanced Computing (SciDAC) program was created to bring together many of the nation's top researchers to develop new computational methods for tackling some of the most challenging scientific problems.
Scientific Discovery Through Advanced Computing
Scientific computing, including modeling and simulation, is crucial for research problems that are not solvable by traditional theoretical and experimental approaches, are hazardous to study in the laboratory, or are time-consuming or expensive to solve by traditional means. Beyond the scientific computing and computational science research embedded in the Office of Science (SC) Core Programs, SC invests in a portfolio of coordinated research efforts directed at exploiting the emerging capabilities of high performance computing. The research projects in this portfolio respond to the extraordinary difficulties of realizing sustained peak performance for those scientific applications that require high performance computing capabilities to accomplish their research goals.
SciDAC began in 2001 to develop the scientific computing software and hardware infrastructure needed to use terascale computers to advance DOE research programs in basic energy sciences, biological and environmental research, fusion energy sciences, and high-energy and nuclear physics. As supercomputers evolved from terascale systems to petascale and multi-core hybrid architectures, the SciDAC program was re-competed in 2006 and in 2011 to meet the accompanying challenges, and the partnerships were extended to include the DOE National Nuclear Security Administration (NNSA).
SciDAC was re-competed a fourth time in 2017 to enable scientific breakthroughs on pre-exascale computing architectures. The partnerships now include DOE’s Office of Nuclear Energy in addition to all 6 SC programs. SciDAC projects pursue computational solutions to challenging problems in climate science, fusion research, high-energy physics, nuclear physics, astrophysics, material science, chemistry, particle accelerators, and nuclear fuels, and ensure that progress at the frontiers of science is enhanced by advances in computational technology, most pressingly, the emergence of the hybrid and many-core architectures and machine learning techniques. The SciDAC program is recognized, both nationally and internationally, as the leader in accelerating the use of high-performance computing to advance the state of knowledge in science applications. View historical information on the previous portfolios.
SciDAC projects are collaborative basic research efforts involving teams of physical scientists, mathematicians, computer scientists, and computational scientists working on major software and algorithm development to conduct complex scientific and engineering computations on leadership-class and high-end computing systems at a level of fidelity needed to simulate real-world conditions. Research funded under the SciDAC program addresses the interdisciplinary problems inherent in high performance computing and problems that cannot be addressed by a single investigator or small group of investigators. View the original SciDAC Program Plan.
Last updated: 10 January 2020