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CSE Seminar
By: Richard (Rich) Vuduc
Georgia Institute of Technology
School of Computational Science and Engineering
Date: Friday, October 28, 2011
Time: 2:00PM-3:00PM, EST
Location: Klaus 2447
For more information please contact Dr. Alexander Gray at agray@cc.gatech.edu
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Title:
What does GPU computing really mean for high-end systems?
Abstract:
Between the years 2018 and 2020, the first exascale supercomputers, capable of a staggering O(10^18) operations per second, will come online. Most high-performance computing analysts are
betting that architectures based on GPU-like processors---that is, graphics co-processors having unprecedented levels of peak performance, processor concurrency, and memory bandwidth---may be the
most viable path toward energy-efficient exascale computing.
But is this a sure bet? In this talk, I'll return to parallel-algorithmic first principles to summarize my research lab's current thinking on this question. Furthermore, I'll ask what
implications our answer for high-end systems might have on the architectures of all classes of computing systems. I will try to limit my formal remarks to highly-debatable statements delivered in ~ 35-40
minutes, to leave time for what I hope will be an active audience discussion.
Bio:
Richard (Rich) Vuduc is an assistant professor in the School of Computational Science and Engineering. His research lab, the HPC Garage (hpcgarage.org), is interested in high-performance computing
with focus areas in parallel algorithms, performance analysis, tuning, and debugging. He received an NSF CAREER award in 2010 and was an invited member of DARPA's 2009-2010 Computer Science Study Panel. Most
recently, his lab was a part of the Georgia Tech team that won the 2010 Gordon Bell Prize.
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