Acceleration of Monte-Carlo Molecular Simulations on Hybrid Computing Architectures
Institute of Computer Architecture and Computer Engineering, University of Stuttgart, Pfaffenwaldring 47, D-70569, Germany
30th IEEE International Conference on Computer Design (ICCD), 2012
@article{braun2012acceleration,
title={Acceleration of Monte-Carlo Molecular Simulations on Hybrid Computing Architectures},
author={Braun, C. and Holst, S. and Wunderlich, H.J. and Castillo, J.M. and Gross, J.},
year={2012}
}
Markov-Chain Monte-Carlo (MCMC) methods are an important class of simulation techniques, which execute a sequence of simulation steps, where each new step depends on the previous ones. Due to this fundamental dependency, MCMC methods are inherently hard to parallelize on any architecture. The upcoming generations of hybrid CPU/GPGPU architectures with their multi-core CPUs and tightly coupled many-core GPGPUs provide new acceleration opportunities especially for MCMC methods, if the new degrees of freedom are exploited correctly. In this paper, the outcomes of an interdisciplinary collabora- tion are presented, which focused on the optimal parallel mapping of a MCMC molecular simulation from thermodynamics to hybrid CPU/GPGPU computing systems. While the mapping is designed for upcoming hybrid architectures, the implementation of this approach on a NVIDIA Tesla system already leads to a substantial speedup of more than 87x despite the additional communication overheads.
November 5, 2012 by hgpu
