Code modernization strategies for short-range non-bonded molecular dynamics simulations

被引:0
作者
Vance, James [1 ]
Xu, Zhen-Hao [1 ]
Tretyakov, Nikita [1 ]
Stuehn, Torsten [2 ]
Rampp, Markus [3 ]
Eibl, Sebastian [3 ]
Junghans, Christoph [4 ]
Brinkmann, Andre [1 ]
机构
[1] Johannes Gutenberg Univ Mainz, Zentrum Datenverarbeitung, Mainz, Germany
[2] Max Planck Inst Polymer Res, Mainz, Germany
[3] Max Planck Comp & Data Facil, Garching, Germany
[4] Los Alamos Natl Lab, Appl Comp Sci Grp, Los Alamos, NM USA
关键词
Molecular dynamics; High performance computing; HPX; MPI; ESPResSo plus plus; HPX;
D O I
10.1016/j.cpc.2023.108760
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Modern HPC systems are increasingly relying on greater core counts and wider vector registers. Thus, applications need to be adapted to fully utilize these hardware capabilities. One class of applications that can benefit from this increase in parallelism are molecular dynamics simulations. In this paper, we describe our efforts at modernizing the ESPResSo++ simulation package for molecular dynamics by re-structuring its particle data layout for efficient memory accesses and applying vectorization techniques to benefit the calculation of short-range non-bonded forces, which results in an overall three times speedup and serves as a baseline for further optimizations. We also implement fine-grained parallelism for multi-core CPUs through HPX, a C++ runtime system which uses lightweight threads and an asynchronous many-task approach to maximize concurrency. Our goal is to evaluate the performance of an HPX-based approach compared to the bulk-synchronous MPI-based implementation. This requires the introduction of an additional layer to the domain decomposition scheme that defines the task granularity. On spa-tially inhomogeneous systems, which impose a corresponding load-imbalance in traditional MPI-based approaches, we demonstrate that by choosing an optimal task size, the efficient work-stealing mecha-nisms of HPX can overcome the overhead of communication resulting in an overall 1.4 times speedup compared to the baseline MPI version.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons .org /licenses /by-nc -nd /4 .0/).
引用
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页数:12
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