Stony Brook University’s Institute for Advanced Computational Science (IACS), together with the University at Buffalo, has received a $13.77 million grant from the U.S. National Science Foundation (NSF) to develop a national supercomputing resource. The project, titled “Sustainable Cyber-infrastructure for Expanding Participation,” aims to provide advanced computing and data capabilities for researchers across the United States.
The grant will fund the acquisition and operation of a high-performance computer that is designed to meet increasing demands in artificial intelligence research and other scientific fields that need significant memory and processing power. This new system will be made available to researchers, students, and educators nationwide to support scientific discoveries and workforce development.
The supercomputer will feature AmpereOne M Advanced Reduced Instruction Set Computer (RISC) Machine processors, known for their low cost and energy efficiency, especially in AI inference tasks common in academic research computing. In addition, Qualcomm Cloud AI inference accelerators will be included to further boost energy efficiency and enable use of large AI models. These technologies have been widely used in commercial cloud environments but are being deployed in academia for the first time through this initiative.
According to IACS director Robert J. Harrison: “This project employs a comprehensive, multilayered strategy, with regional and national elements to ensure the widest possible benefits. The team will collaborate with multiple initiatives and projects, to reach a broad audience that spans all experience levels from high school students beginning to explore science and technology to faculty members advancing innovation through scholarship and teaching.”
Co-principal investigator Nikolay Simakov of the University at Buffalo Center for Computational Research stated: “The University at Buffalo is excited to partner with Stony Brook on this new project that will advance research, innovation and education by expanding the nation’s cyber-infrastructure to scientific disciplines that were not high performance computing-heavy prior to the AI boom, as well as expanding to non-R1 universities, which also didn’t have much of high-performance computing usage in the past.”
The NSF funding is intended not only for technological advancement but also for broadening participation among underrepresented groups in science fields. The new system is expected to benefit areas such as life sciences and computational linguistics—fields not typically served by existing national resources—by providing optimized software applications tailored for these workloads.
The award aligns with NSF’s mission by supporting projects evaluated on intellectual merit and broader impacts criteria.