MRI/MII: Acquisition of Collaborative High Performance Computing and Visualization Cluster

Old Dominion University Research Foundation, Norfolk VA

Investigators

Abstract

EIA-0216541 Stephen A. Zahorian R. Bowen Loftin Old Dominion University MRI/MII: Acquisition of Collaborative High Performance Computing and Visualization Center This proposal from an MII institution, establishing a Beowulf cluster for High Performance Computing (HPC) and visualization, aims at enabling, supporting, and enhancing research and education in modeling and simulation. The main applications addressed use a variety of numerically intensive algorithms, which require many "runs" of a base computational algorithm in order to view the big picture. Technical areas which will benefit from the infrastructure include enterprise modeling and simulation and visualization, high performance computing in areas such as PDE solvers and bioinformatics, control systems modeling, automatic speech recognition, and physical electronics simulations. Current specific research activities at ODU include: 1. Modeling and Simulation Research, 2. A JSC Augmented Reality Trainer for International Space Station Space Lab Window Assembly, 3. Virtual Environments for Training, 4. VMASC Battle Lab (war gaming, human computer interfaces, visualization and distributed simulation) 5. Center for Computational Science, 6. Terascale Optimal PDE Simulations, 7. Bioinformatics, 8. Speech Communications Research, 9. Physical electronics simulations (Bio-electrics, Nanoelectronics, Lattice Boltzmann Simulations, and 10. Systems Research on Life Critical Control Systems. The computational cluster will have approximately 50 nodes on the main campus and a number of similar notes at the modeling and simulation center in Suffolk. Coupled via gigabit network and loosely coupled between the two subclusters, the machines within each local cluster will use public domain (e.g., Linux based) operating systems and scheduling such that computationally intensive investigations can be initiated from various locations. The equipment will support faculty and student training providing hands-on experience in advanced computing research.