Acceleration of Dynamic n-Tuple Computations in Many-Body Molecular Dynamics
Authors: 
Patrick E. Small, Kuang Liu, Subodh Tiwari, Rajiv K. Kalia, Aiichiro Nakano, Ken-ichi Nomura, Priya VashishtaAuthors Info & Claims
Pages 159 - 170
Abstract
Computation on dynamic n-tuples of particles is ubiquitous in scientific computing, with an archetypal application in many-body molecular dynamics (MD) simulations. We propose a tuple-decomposition (TD) approach that reorders computations according to dynamically created lists of n-tuples. We analyze the performance characteristics of the TD approach on general purpose graphics processing units for MD simulations involving pair (n = 2) and triplet (n = 3) interactions. The results show superior performance of the TD approach over the conventional particle-decomposition (PD) approach. Detailed analyses reveal the register footprint as the key factor that dictates the performance. Furthermore, the TD approach is found to outperform PD for more intensive computations of quadruplet (n = 4) interactions in first principles-informed reactive MD simulations based on the reactive force-field (ReaxFF) method. This work thus demonstrates the viable performance portability of the TD approach across a wide range of applications.
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Index Terms
- Acceleration of Dynamic n-Tuple Computations in Many-Body Molecular Dynamics
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Published In
January 2018
322 pages
ISBN:9781450353724
DOI:10.1145/3149457
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- IPSJ: Information Processing Society of Japan
- Cybermedia Center, Osaka University: Cybermedia Center, Osaka University
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Association for Computing Machinery
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Published: 28 January 2018
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HPC Asia 2018
HPC Asia 2018: International Conference on High Performance Computing in Asia-Pacific Region
January 28 - 31, 2018
Tokyo, Chiyoda, Japan
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HPCAsia '18 Paper Acceptance Rate 30 of 67 submissions, 45%;
Overall Acceptance Rate 69 of 143 submissions, 48%
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