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	SCHEDULE: NOV 11-17, 2006 Data-Driven Time Parallelization Session: Poster Reception Event Type: Poster Time: 5:15pm - 7:15pm Author(s): Lei Ji, Yanan Yu, Namas Chandra, Hugh Nymeyer, Ashok Srinivasan Location: Ballroom Corridor Abstract: We present a new approach to parallelization of important scientific applications. It is based on the observation that results of prior, related, simulations are often available. We use such data to parallelize the time domain. We demonstrate the effectiveness of our approach in Molecular Dynamics (MD) simulations, which are widely used in nano and nano-bio sciences. An important limitation of MD is that the time-step size is around a femto-second. So a large number of time-steps are required to simulate to realistic time scales. Conventional parallelization is of limited effectiveness here -- the most scalable codes currently are not efficient at granularities finer than several milliseconds per iteration. Using our approach, Carbon Nanotube simulations scale to granularities as fine as around ten microseconds per iteration. We also present results on protein unfolding simulations of AFM pulling, where we obtain additional one order of magnitude scalability over conventional parallelization. Chair/Author Details: Lei Ji Florida State University Yanan Yu Florida State University Namas Chandra Florida State University Hugh Nymeyer Florida State University Ashok Srinivasan Florida State University
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