MRI: Acquisition of a High-Performance Computational System for OAK Region to Enable Computing and Data Driven Discovery

This project will acquire and deploy a high-performance computing (HPC) system to serve the researchers and educators in the broad Oklahoma-Arkansas-Kansas (OAK) region. Computational modeling, simulations, and data analytics are essential tools for new discoveries across all areas of science, engineering and mathematics. In particular, modern research breakthroughs are being driven by vast amounts of data enabled by computing and memory capacity, often combined with machine-learning/artificial intelligence (ML/AI) techniques.

This system will seed the growth of a collaborative HPC ecosystem in the region, serving the needs of experienced users and enabling first time users, especially from small and under-served institutions. Technical know-how exchange, regular seminars, and conferences will promote collaborative research endeavors of regional and national importance. Hands on training of graduate, undergraduate and high-school students in computational and data sciences will broadly improve the skill-sets of the science and engineering workforce in the OAK region.

The deployed system will harness the power of the latest CPUs, cutting-edge graphics processing units (GPUs), 100 Terabytes of aggregate memory, an HDR InfiniBand interconnect, and Petabyte-scale high-speed storage. This system consisting of several types of nodes (CPUs-only, mid-range GPUs, and high-end GPUs) will provide close to 100 million-core hours of computing and will serve as a vital regional resource for science and engineering research.

Initial research areas to be served by the system include biology, human and animal health, agriculture, environment research, chemistry and chemical engineering, semiconductor materials research, cybersecurity and social network modeling, renewable energy research, seismology, high-energy physics, and medical physics. This significantly improved computing and data analysis capabilities provided by this system will greatly benefit scientific productivity.

Furthermore, the instrument will make it possible for faculty to include HPC and data analysis techniques in the STEM education curriculum, leading to computational thinking becoming a part of research in the minds of the next generation of scientists. Lowering the barrier of entry to HPC will also help improve the education and training of women, minorities and under-represented groups.

This system will also contribute computing resources beyond the OAK region through collaborative mechanisms such as the Partnership to Advance Throughput computing (PATh) and the Open Science Grid (OSG).

This project is jointly funded by the Major Research Instrumentation (MRI) program, the Established Program to Stimulate Competitive Research (EPSCoR), and the Computer & Information Science & Engineering (CISE) Directorate.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.