MRI: Acquisition of Cyberinfrastructure for Computational Research (CCR)

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Proposal #: CNS 08-21727PI(s): Mellor-Crummey, John Clementi, Cecilia; Nakhleh, Luay; Nordlander, Peter A.; Tezduyar, Tayfun E..Institution: Rice University Houston, TX 80309-0572Title: MRI/Acq.: Acq. of Cyberinfrastructure for Computational Research (CCR)Project Proposed:This project, acquiring instrumentation and operating a computational cluster for research (CCR), enables code development, medium scale computation, preparation of scalable codes for execution on national-scale resources, post-processing and visualization of results from remote supercomputers, and research training. Projects range from development of enabling technologies, such as programming models and performance analysis tools for parallel systems, to computational science and engineering research that includes techniques for automated verification of complex hardware and software designs, data mining of multiple whole genomes, studying large-scale ecological dynamics, determining the properties of nanophotonic structures through simulation, simulating protein dynamics to study flexibility and function, modeling transport properties in biophysical systems, and understanding fluid structure interactions in physiological systems and engineering designs. The increase in the number of CPU hours available for shared research computing contributes to support the explosive growth of computational research. Hence, more tightly coupled computing can be supported at a higher scale; a centralized computing facility can be scheduled for higher utilization; a single system can be operated and administered (rather than collections of cluster for individual research groups, and may effectively on-ramp national resources. Operating this modest-size computational cluster locally complements the TeraGrid and accelerates research. In particular, higher bandwidth and lower latency to the desktop from a local system better supports code development using interactive tools with graphical user interfaces (e.g., for debugging, performance, and scalability analysis, and data visualization) while preparing codes for execution on national-scale resources. Indeed, computation is an indispensable tool for scientific inquiry and complements traditional approaches of theory and experimentation.Broader Impacts:CCR enhances the graduate research and training of hundreds of students and post-doctoral fellows in science and engineering. It provides educational experience for undergraduate and graduate students through its use in courses that integrate high performance computing and computational problem solving. Furthermore, a boot-camp will familiarize students with high performance computing and teach computational problem solving skills. The instrument also contributes to recruiting and serves as an educational tool in the Alliance for the Graduate Education and the Professoriate (AGEP), a successful program in attracting members from underrepresented groups into higher education, thus broadening their educational experience.