MRI-R2: Acquisition: A Hybrid High-Performance GPU/CPU System

Temple University, Philadelphia PA

Investigators

Abstract

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)." Proposal #: 09-58854 PI(s): Wu, Jie, Biswas, Saroj K., Klein, Michael L., Rivin, Igor, Shi, Yuan Institution: Temple University Title: MRI-R2: Acquisition: A Hybrid High-Performance GPU/CPU System Project Proposed: This project, acquiring a hybrid high-performance GPU (graphics processing unit)/CPU system, enables broader heterogeneous computing by deploying multiple types of computing nodes and allowing each to perform the tasks to which it is best suited in traditional CPU-based, GPU based, and hybrid GPU/CPU applications. Satisfying two major research environments in computer and information sciences and scientific computing, the instrument - Serves faculty and students conducting research using existing parallel application software and developing tools for parallel programming and parallel applications of the system, - Serves the center for High Performance Computing and Networking at the institution and the greater Philadelphia region offering services not only to other departments on campus, but also to other institutions in the local community, such as area high schools and local colleges/universities , - Educates and trains providing a computing environment to various science courses for students to gain hands-on experience and offers research training sessions to the local research community; and - Fosters collaboration by supporting joint research with local colleges/universities, in collaboration with other schools in the state, to develop, test, and apply advanced tools for designing and executing parallel programs. Among others, the Center services Chemistry, Computer and Information Sciences, Electrical and Computer Engineering, Mathematics, Physics, and Pulmonary, Critical Care Medicine and Physical Therapy. The instrument specifically supports research projects with broad impact in molecular self assembly, microvessel networks, spatio-temporal data analysis, large-scale system simulation, effective uniformization, fault tolerant computing, etc. and augments existing applications using the GPU as an accelerator enabling some problems to run entirely on the GPU. Broader Impacts: The instrument greatly enhances the current computing facilities at the institution. With its GPU/CPU component, this instrument is the first of its kind of high-performance computing facility in the greater Philadelphia region, an area with a high degree of diversity. This university draws a substantial portion of its students from one of the largest African American populations in the country. Enabling education, training, and collaboration, the instrument contributes to foster economic growth in an area with a high concentration of high-tech and IT-related industries that currently has no high-performance computing and networking center of this magnitude. The region is now able to go beyond minimal services and promote and support collaboration and cooperation across sectors (e.g., higher education and local industry).