Equipment: MRI: Track 1 Acquisition of NVIDIA DGX H100 GPU system for research and education at VCU

Graphic Processing Units (GPUs) have become an essential computational tool in support of a wide range of research areas. This project funds the acquisition of a high-performance GPU cluster to be installed at the Virginia Commonwealth University (VCU) High-Performance Research Computing (HPRC) core user facility, which provides shared university-wide access to high-performance computing clusters for research and education purposes.

The GPU instrumentation will benefit the research and training activities of 22 research groups and impact 400+ users across the entire university. The acquisition advances next-generation research in artificial intelligence, modeling, and simulations across a broad range of disciplines including computer science, engineering, life sciences, and physical sciences.

Further benefits include those to cutting-edge research, research training of graduate and undergraduate students, course and curriculum development, K-12 outreach impacts, and the participation of underrepresented minorities. The new resources will also strengthen interdisciplinary research and broaden collaborative activities across disciplines with local industry and federal laboratories.

The acquisition of a NVIDIA DGX H100 GPU system will significantly expand the GPU computing capacity at VCU to help satisfy the increasing high-performance computing demand across various science & engineering disciplines. The key research projects that will benefit from this equipment are in the areas of machine learning for high-speed data streams, deep learning and quantum machine learning, neuromodulation (transcranial magnetic stimulation and deep brain stimulation), computational chemistry (quantum chemistry), optics and defects in semiconductors (gallium nitride), software vulnerability prediction using deep learning, nanomagnetic materials and nanoscale magnetic devices, real-time pandemic management architecture, secure and flexible medical IoT infrastructure (protection from cyberattacks deployed at network edge components), and ultrafast dissociation dynamics of isolated organic molecular cations.

This project will also support the training of high-school, undergraduate, graduate students and postdoctoral fellows in cutting-edge interdisciplinary research spanning computer science, engineering, physics, and chemistry, strengthening existing ties with nearby HBCUs, as well as expanding K-12 minority outreach programs.

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.