• 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 ›› 2026, Vol. 48 ›› Issue (3): 381-388.

• 高性能计算 •    下一篇

基于事件的蒙特卡罗粒子输运算法设计实现

黎铁军,张建民,李雨函,杨博   

  1. (国防科技大学计算机学院,湖南 长沙 410073) 

  • 收稿日期:2024-07-21 修回日期:2024-10-23 出版日期:2026-03-25 发布日期:2026-03-25
  • 基金资助:
    国家自然科学基金(62072464)

Design and implementation of an event-based Monte Carlo particle transport algorithm

LI Tiejun,ZHANG Jianmin,LI Yuhan,YANG Bo   

  1. (College of  Computer Science and Technology,National University of Defense Technology,Changsha 410073,China)
  • Received:2024-07-21 Revised:2024-10-23 Online:2026-03-25 Published:2026-03-25

摘要: 蒙特卡罗MC粒子输运程序是典型的高性能计算应用。MC粒子输运程序存在基于粒子历史与基于事件2种并行实现方法。代理程序是面向特定体系结构开展大型实际程序性能优化的重要基础,实现基于事件的MC代理程序对研究面向众核体系结构的性能优化非常重要。然而目前没有公开的基于事件方法的代理程序。基于开源项目OpenMC,对基于事件的蒙特卡罗粒子输运算法进行设计,实现了一个新的基于事件的MC粒子输运代理程序。实验结果表明,该代理程序能够有效模拟OpenMC的分支、访存及计算特征,且其代码量不到OpenMC代码量的5%,运行时间仅为OpenMC的7.5%,为基于事件算法的优化研究提供了高效易用的平台。

关键词: 粒子输运模拟, 蒙特卡罗算法, 基于事件的方法, 程序特征提取 ,

Abstract: Monte Carlo particle transport program is a typical high-performance computing  (HPC) application. There are two  parallel methods for MC particle transport programs: history-based method and event-based method. Proxy programs serve as a crucial foundation for optimizing the performance of large-scale practical programs tailored to specific architectures, and the implementation of an event-based MC proxy program is of great importance for researching performance optimization for many-core architectures. However, there are no publicly available event-based proxy programs. Based on the open source project OpenMC, an event-based Monte Carlo particle transport algorithm is designed, and then a new event-based MC proxy program is implemented. Experimental results show that this proxy program can effectively simulate the branching, memory access, and computational characteristics of OpenMC, with its code size being less than 5% of that of OpenMC. Moreover, its runtime is merely 7.5% of OpenMC’s, providing an efficient and user-friendly platform for optimization research based on event-based algorithms. 

Key words: particle transport simulation, Monte Carlo algorithm, event-based method, program feature extraction