Software infrastructures for Chinese supercomputers from the perspective of lattice QCD applications

Ming GONG; Xiangyu JIANG; Ying CHEN; Zhaofeng LIU

doi:10.11959/j.issn.2096-0271.2021047

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Software infrastructures for Chinese supercomputers from the perspective of lattice QCD applications

TOPIC: BIG DATA PROCESSING SYSTEM IN CHINA’S HOMEMADE COMPUTING ENVIRONMENT | 更新时间：2024-06-03

- Software infrastructures for Chinese supercomputers from the perspective of lattice QCD applications
- Big data research Vol. 7, Issue 5, Pages: 2021047(2021)
- 作者机构：
  
  1. 中国科学院高能物理研究所，北京 100049
  2. 中国科学院大学，北京 100049
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2021047
  CLC： O4-39，O411.2，O572.24+3
- Online First：2021-09，
  
  Published：15 September 2021
- 稿件说明：
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Ming GONG, Xiangyu JIANG, Ying CHEN, et al. Software infrastructures for Chinese supercomputers from the perspective of lattice QCD applications[J]. Big data research, 2021, 7(5): 2021047.
DOI：

Ming GONG, Xiangyu JIANG, Ying CHEN, et al. Software infrastructures for Chinese supercomputers from the perspective of lattice QCD applications[J]. Big data research, 2021, 7(5): 2021047. DOI： 10.11959/j.issn.2096-0271.2021047.

摘要

格点量子色动力学（LQCD）是用数值模拟方法研究基本粒子的重要科学领域，因其巨大的数据量和计算规模而成为国际上超级计算机的主要科研应用之一。随着国产新一代超级计算机的发展，LQCD的计算软件由于其传统编程模型的限制，面临着更新换代的关键节点。从格点量子色动力学的视角出发，分析大规模科学应用软件对底层基础软件的需求特点，面向国产超算平台的发展方向，提出适配于大规模高效异构计算和大数据处理的新编程模型，为国产超算环境的基础软件建议了一个有潜力的发展方向。

Abstract

Lattice QCD is a frontier scientific field for studying elementary particles by numerical simulation methods

which has become one of the major scientific research applications of supercomputers.With the rapid development of Chinese supercomputers

the LQCD softwares need to be refactored due to the limitation of its traditional programming model.The characteristics of scientific applications on super computers from the perspective of lattice QCD were reviewed.A novel programming model targeted to Chinese super computers was proposed to adapt large-scale scientific applications with big data processing

which is a promising development direction for the basic softwares of Chinese supercomputing ecosystem.

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references

ABI B , ALBAHRI T , AL-KILANI S , , et al . Measurement of the positive muon anomalous magnetic moment to 0.46 ppm [J ] . Physical Review Letters , 2021 , 126 ( 14 ): 141801 .

胡正丁 , 薛巍 . 面向异构众核超级计算机的大规模稀疏计算性能优化研究 [J ] . 大数据 , 2020 , 6 ( 4 ): 40 - 55 .

HU Z D , XUE W . Research on performance optimization for largescale sparse computation over many-core heterogenous supercomputer [J ] . Big Data Research , 2020 , 6 ( 4 ): 40 - 55 .

张淼 , 周宇 , 陈建海 , 等 . LQCD Dslash在神威·太湖之光上的研究分析与MPI实现 [J ] . 计算机科学与探索 , 2019 , 13 ( 10 ): 1664 - 1676 .

ZHANG M , ZHOU Y , CHEN J H , et al . Analysis and MPI implementation of LQCD Dslash on Sunway TaihuLight [J ] . Journal of Frontiers of Computer Science ＆Technology , 2019 , 13 ( 10 ): 1664 - 1676 .

ZHANG Z X , LUAN Z Z , XU C Y , et al . Accelerating lattice QCD on sunway many-core processor [C ] // Proceedings of 2018 IEEE International Conference on Parallel and Distributed Processing with Applications,Ubiquitous Computing and Communications,Big Data and Cloud Computing,Social Computing and Networking,Sustainable Computing and Communications . Piscataway:IEEE Press , 2018 : 605 - 612 .

毕玉江 , 周超 , 吴郁飞 , 等 . 格点量子色动力学Grid数值模拟软件的并行计算特征分析 [J ] . 计算机系统应用 , 2020 , 29 ( 7 ): 199 - 204 .

BI Y J , ZHOU C , WU Y F , et al . Parallel computing feature analysis of Grid numerical simulation software for lattice quantum chromodynamics [J ] . Computer Systems ＆ Applications , 2020 , 29 ( 7 ): 199 - 204 .

BI Y J , XIAO Y , GUO W Y , et al . Lattice QCD GPU inverters on ROCm platform [C ] // Proceedings of the 24th International Conference on Computing in High Energy and Nuclear Physics .[S.l.:s.n. ] , 2020 :09008.

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