High Performance Computing Algorithm and Software for Heterogeneous Computing

被引：0
|
作者：
Xu S. [1 ,2 ]
Wang W. [1 ,2 ]
Zhang J. [1 ,2 ]
Jiang J.-R. [1 ,2 ]
Jin Z. [1 ,2 ,3 ]
Chi X.-B. [1 ,2 ]
机构：
[1] Computer Network Information Center, Chinese Academy of Sciences, Beijing
[2] Center of Scientific Computing Applications and Research, Chinese Academy of Sciences, Beijing
[3] Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou
来源：
Ruan Jian Xue Bao/Journal of Software | 2021年 / 32卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Heterogeneous computing; High performance computing; Parallel algorithm; Scientific computing software;
D O I：
10.13328/j.cnki.jos.006008
中图分类号：
学科分类号：
摘要：
It is very important to develop high performance computing algorithm and software adapting China heterogeneous supercomputer. This has also great significance in minimizing the gap between China's HPC hardware and HPC software. Firstly, the article briefly introduces current trend and challenges of high-performance computing application software and analyzes computing algorithm characteristics of various typical high performance computing applications including N-body simulation in computing cosmology, earth system model, computational material phase field dynamics, molecular dynamics, quantum chemistry, and lattice QCD. Secondly, solution to use domestic heterogeneous computing system has been discussed and typical application algorithms, common questions of software including core algorithm, development of algorithm, strategies of optimizing codes have been summarized as well. Finally, a summary of high-performance computing algorithms and software for heterogeneous computing is given. © Copyright 2021, Institute of Software, the Chinese Academy of Sciences. All rights reserved.
引用
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页码：2365 / 2376
页数：11
相关论文
共 38 条
  • [1] Ezell SJ, Atkinson RD., The vital importance of high performance computing to U.S. competitiveness, (2016)
  • [2] Dongarra J, Et al., Supercomputer Top500 list, (2019)
  • [3] Jin Z, Lu ZH, Li HY, Chi XB, Sun JC., Origin of high performance computing-Current status and developments of scientific computing applications, Bulletin of Chinese Academy of Sciences, 34, 6, pp. 625-639, (2019)
  • [4] US lattice quantum chromodynamics, (2019)
  • [5] Carleton DeTar, MILC code, (2019)
  • [6] Boyle P, Cossu G, Yamaguchi A, Portelli A., Grid: A next generation data parallel C++ QCD library, (2015)
  • [7] Clark MA, Babich R, Barros K, Brower R, Rebbi C., Solving lattice QCD systems of equations using mixed precision solvers on GPUs, Computer Physics Communication, 181, pp. 1517-1528, (2010)
  • [8] Plimpton S., Fast parallel algorithms for short-range molecular dynamics, Journal of Computational Physics, 117, pp. 1-19, (1995)
  • [9] Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K., Scalable molecular dynamics with NAMD, Journal of Computational Chemistry, 26, 16, pp. 1781-1802, (2005)
  • [10] Valiev M, Bylaska EJ, Govind N, Kowalski K, Straatsma TP, van Dam HJJ, Wang D, Nieplocha J, Apra E, Windus TL, de Jong WA., NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations, Computer Physics Communications, 181, 9, pp. 1477-1489, (2010)
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