• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2020, Vol. 42 ›› Issue (11): 1922-1928.

• 高性能计算 • 上一篇    下一篇

面向天河2A系统的基于蒙特卡罗方法的粒子输运异构协同计算

李彪1,刘杰1,2   

  1. (1.国防科技大学并行与分布处理国家重点实验室,湖南 长沙 410073;
    2.复杂系统软件工程湖南省重点实验室,湖南 长沙 410073)
  • 收稿日期:2020-06-10 修回日期:2020-07-30 接受日期:2020-11-25 出版日期:2020-11-25 发布日期:2020-11-26
  • 基金资助:
    国家重点研发计划(2017YFB0202104);湖南省自然科学基金(2019JJ40339);国防科技大学科研项目(ZK180301)

Heterogeneous cooperative computing of particle transport based on Monte Carlo method on the Tianhe 2A system

LI Biao1,LIU Jie1,2   

  1. (1.Science and Technology on Parallel and Distributed Processing Laboratory,
    National University of Defense Technology,Changsha 410073;
    (2.Hunan Key Laboratory of Software Engineering for Complex Systems,Changsha 410073,China)
  • Received:2020-06-10 Revised:2020-07-30 Accepted:2020-11-25 Online:2020-11-25 Published:2020-11-26

摘要: 粒子输运模拟在核科学领域、医疗放射治疗领域中占有重要的地位。基于MC方法设计和开发了面向天河2A系统的粒子输运异构协同算法;基于天河2A系统的异构通信模式BCL和ACL,提出了一种CPU与加速器Matrix2000之间的简单高效的对称通信模式;在Matrix2000加速器端,通过OpenMP指令开发程序的线程级并行;优化了原MC程序串行数据收集通信模式,提出了新的二叉树通信模式,极大地减少了通信时间。实现的基于CPU/Matrix2000异构协同计算的并行程序,在天河2A系统上进行测试,大规模测试可以扩展到45万核,相对5万核并行效率保持在22.54%。


关键词: 粒子输运, 异构协同计算, 蒙特卡罗方法, OpenMP, 国产加速器

Abstract: Particle transport simulation plays an important role in the field of nuclear science and medical radiation therapy. Based on Monte Carlo method, this paper proposes a heterogeneous cooperative algorithm of particle transport on the Tianhe2A system. Based on the asynchronous communication modes (BCL and ACL) of the Tianhe 2A system, a simple and efficient symmetric communication mode between the CPU and the Matrix2000 accelerator is proposed. On the Matrix2000 accelerator, the threadlevel parallelism of the program is developed through OpenMP instructions. The original serial data collection communication mode is optimized, and a new communication mode based on binary tree structure is proposed, which greatly reduces the communication time. On the Tianhe2A system, the parallel program based on CPU/Matrix2000 heterogeneous collaborative computing can be scaled up to 450k cores, and the parallel efficiency compared to 50k cores is stabilized at 22.54%.

Key words: particle transport, heterogeneous collaborative computing, Monte Carlo method, OpenMP, domestic accelerator