MRI: Acquisition of a Hybrid GPU Computing Cluster High-End Applications in Science and Engineering

Kansas State University, Manhattan KS

Investigators

Abstract

Proposal #: CNS 11-26709 PI(s): Andresen, Daniel; Caragea, Doina; Dodds, Walter K; Esry, Brett; Steward, David R. Institution: Kansas State University Title: MRI/ Acq.: A Hybrid GPU Computing Cluster High-End Applications in Science and Engineering Project Proposed: This project, acquiring a hybrid computing cluster for high-end applications in science and engineering, services, among others, bioinformatics, ecological modeling, and physics. GPU-based computing support for distributed memory parallel applications constitutes a specific novel feature of the cluster. The work aims to support the following activities: - Modeling genomes, hyper-extractive economies, and ecological forecasting (by bringing much greater computational power) and, - Enabling new science utilizing the instrument to develop new algorithms in physics modeling and genomics. Broader Impacts: Mainly, the multidisciplinary nature of the proposed research provides the broader impacts. Expected are large broader impacts on basic physics research. It is expected to also impact on medicine through the development of better molecular models to view how our proteins and membranes interact. Planned are training activities of a new generation of researchers in tools and techniques for high-performance computing. The PIs would build on the broad past experience in preparing widely-used undergraduate and graduate educational materials, allowing students to perform real-world projects and impacting K-12 and STEM education. Hence, the project aims to significantly enhance and integrate our educational efforts at the K-12, undergraduate and graduate levels in bioinformatics.