Hetrogenous Parallel Computing

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With processor core counts doubling every 18-24 months and penetrating all markets from high-end servers in supercomputers to desktops and laptops down to even mobile phones, we sit at the dawn of a world of ubiquitous parallelism, one where extracting performance via parallelism is paramount. That is, the "free lunch" to better performance, where programmers could rely on substantial increases in single-threaded performance to improve software, is over. The burden falls on developers to exploit parallel hardware for performance gains. But how do we lower the cost of extracting such parallelism, particularly in the face of the increasing heterogeneity of processing cores? To address this issue, this talk will present a vision for an ecosystem for delivering accessible and personalized supercomputing to the masses, one with a heterogeneity of (hardware) processing cores on a die or in a package, coupled with enabling software that tunes the parameters of the processing cores with respect to performance, power, and portability via a benchmark suite of computational dwarfs and applications.

Bio: Wu Feng is an Elizabeth & James Turner Fellow and Associate Professor of Computer Science and Electrical & Computer Engineering at Virginia Tech, where he directs the Synergy Laboratory and serves as the VT site co-director of the NSF Center for High-Performance Reconfigurable Computing (CHREC). He is also an adjunct faculty in the Virginia Bioinformatics Institute at Virginia Tech and in the Dept. of Cancer Biology and Translational Science Institute at Wake Forest University. His research interests in efficient parallel computing sits at the synergistic intersection of computer architecture, systems software, middleware, and applications software and ranges from core computer science research to highly interdisciplinary research. Of recent note is a new supercomputing resource that will support the above research and research campus-wide: HokieSpeed.

Dr. Feng received a B.S. in Electrical & Computer Engineering and Music (Honors) and an M.S. in Computer Engineering from Penn State University in 1988 and 1990, respectively. He earned a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1996. His previous professional stints include IBM T.J. Watson Research Center, NASA Ames Research Center, Vosaic, University of Illinois at Urbana-Champaign, Purdue University, The Ohio State University, Orion Multisystems, and Los Alamos National Laboratory. He is a Distinguished Member of the ACM, Senior Member of the IEEE, and two-time designee of HPCwire's Top People to Watch List.

Feng's Website: http://people.cs.vt.edu/~feng/

Parallelism, Supercomputing, Multicore