We are excited to receive a $900,000 Major Research Instrumentation (MRI) Track 1 grant from the National Science Foundation (Award #2511818) to acquire a state-of-the-art multi-accelerator computing architecture for advanced scalable computing research.
Dr. Susmit Shannigrahi is a co-Principal Investigator on the project, teaming up with PI Anthony Skjellum and co-PIs Syed Rafay Hasan, Muhammad Ismail, and Amani Altarawneh, all at Tennessee Technological University. The team also includes collaborators from the University of Tennessee, Chattanooga and the University of Tennessee, Knoxville.
The instrument itself is a six-node high-performance computing cluster built around a rare combination of three accelerator technologies working in concert: Accelerated Processing Units (APUs), Data Processing Units (DPUs), and Field-Programmable Gate Arrays (FPGAs). Bringing all three together in one fully networked system gives researchers a rare opportunity to study how future computers can be designed and programmed to work faster and more efficiently together, and to apply that capability to real scientific and engineering problems.
Planned research spans real-time inference of collaborative deep neural networks, hyperparameter optimization and neural architecture search, AI-driven blockchain security for the Internet of Things, parallel programming models across heterogeneous hardware, smarter network computation, distributed quantum computing simulation, name-based compute and data placement, AI-driven networking and communications, and AI/ML-informed methods for generating fast collective algorithms. The results are expected to inform the design of future cluster and leadership-class computer architectures.
The instrument will also support hands-on research training for undergraduate, master’s, and doctoral students, giving them access to emerging accelerator hardware not typically available on public computing systems.
The award runs from August 1, 2026 through July 31, 2029. Full award details are available via NSF Award Search.