The MuST program, the recipient of $150,000 in NSF improvement funding, radically reduces the complexity of simulating complex materials

$7-million NSF Characteristic Science Applications program to further develop 21 scientific software projects

Further development of a computer program to improve predictions of the physical behavior of industrially important materials, designed with leadership from PSC, has been awarded $150,000 through the National Science Foundation (NSF)-funded Characteristic Science Applications (CSA) program.

The 21 computer applications awarded reflect the broad range of science domains and computational approaches — from language, to method, to workflow — that researchers will run on future supercomputers. They were selected by the community of large-scale high performance computing (HPC) users.

The PSC-led program, called MuST, is a new, open-source supercomputing code that radically reduces the complexity of simulating complex materials. A key advance of MuST over other comparable methods is that it promises predictions of the physical and electronic behavior of samples large enough to be relevant to the real world, and more quickly. The program was developed by a national collaboration of scientists led by Yang Wang, senior computational scientist at PSC, with funding by the NSF.

“The CSA funding will help us to allocate resources for improving the software engineering of the MuST code,” Wang said, with an ultimate goal of “boosting the performance of the code to the next level: A more than 10-times speedup on the future NSF leadership system. The CSA funding will also help the MuST code meet the increasing demands from the scientific community for high performance and large-scale ab initio calculation of disordered [chemical] structures.”

The 21 teams selected under CSA will each be awarded $150,000 for the first year of study and design. In total, NSF awarded $7 million over two years to TACC to support the CSA program. The CSA program received 140 submissions, covering all areas of science, and involving 167 institutions in 38 states.

“Extensive engagement with the diverse research community is critical to the design of LCCF,” the NSF’s future Leadership Class Computing Facility, said Manish Parashar, director of NSF’s Office of Advanced Cyberinfrastructure. “NSF appreciates the overwhelming response from the community to the CSA program. This will ensure that the future facility will have the broadest impact and sustain our nation’s leadership in science and engineering.”