MPI在蒙特卡罗程序GMT中的应用和发展

许建亚; 杨磊; 张延师; 张勋超; 付芬; 张雅玲; 杨琼

doi:10.11804/NuclPhysRev.34.02.204

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MPI在蒙特卡罗程序GMT中的应用和发展

许建亚, 杨磊, 张延师, 张勋超, 付芬, 张雅玲, 杨琼

文章导航 > 原子核物理评论 > 2017 > 34(2): 204-210

许建亚, 杨磊, 张延师, 张勋超, 付芬, 张雅玲, 杨琼. MPI在蒙特卡罗程序GMT中的应用和发展[J]. 原子核物理评论, 2017, 34(2): 204-210. doi: 10.11804/NuclPhysRev.34.02.204

引用本文:

XU Jianya, YANG Lei, ZHANG Yanshi, ZHANG Xunchao, FU Fen, ZHANG Yaling, YANG Qiong. Application and Development of MPI in Monte Carlo Code GMT[J]. Nuclear Physics Review, 2017, 34(2): 204-210. doi: 10.11804/NuclPhysRev.34.02.204

Citation:

XU Jianya, YANG Lei, ZHANG Yanshi, ZHANG Xunchao, FU Fen, ZHANG Yaling, YANG Qiong. Application and Development of MPI in Monte Carlo Code GMT[J]. Nuclear Physics Review, 2017, 34(2): 204-210. doi: 10.11804/NuclPhysRev.34.02.204

MPI在蒙特卡罗程序GMT中的应用和发展

doi: 10.11804/NuclPhysRev.34.02.204

许建亚^1,2,
杨磊^2,,
张延师²,
张勋超²,
付芬²,
张雅玲²,
杨琼^1,2

1.
中国科学技术大学, 合肥 230026;
2.
中国科学院近代物理研究所, 兰州 730000

基金项目: 中国科学院战略性先导科技专项（XDA03030100）

详细信息

作者简介:
许建亚(1988-),男,甘肃定西人,研究实习员,从事高性能计算研究：E-mail:xujianya@impcas.ac.cn

通讯作者: 杨磊,E-mail:lyang@impcas.ac.cn。

中图分类号: TL329

Application and Development of MPI in Monte Carlo Code GMT

1.
University of Science and Technology of China, Hefei 230026, China;
2.
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China

Funds: Strategic Priority Research Program of Chinese Academy of Sciences(XDA03030100)

摘要: 针对ADS颗粒靶概念的研究和设计，中国科学院近代物理研究所自主研发了蒙特卡罗模拟软件GMT。为了提高GMT程序的计算效率，研究了MPI在GMT中的应用和发展，实现了大规模随机数在进程中的随机分配，并采用快速读写文件的方式替代了MPI相关数据通信函数，极大地提高了计算效率。并研究了不同规模计算实例进程数、加速比、效率之间的关系，确定了最大加速进程数及并行效率最高时的进程数，为科研工作者在计算资源和计算效率之间选择最优计算方案提供了科学依据。MPI在GMT中的成功应用使计算资源得到了充分、高效的利用，极大地提高了计算效率，解决了蒙特卡罗方法中大规模事件模拟计算时间长、计算不稳定等问题，在散裂靶大规模扫描计算中发挥了重要的作用。

For the research and design of the ADS granular-flow target concept, the Institute of Modern Physics, CAS has developed a Monte Carlo simulation software (GPU-accelerated Monte Carlo Transport program, GMT). In order to improve the computational efficiency of the GMT program, development and application of MPI in GMT were studied, to realize random distribution of the large-scale random number in the sub processes. Rapid reading and writing files were employed instead of the MPI data communication function, which greatly improves the computational efficiency. Different scale calculations were performed to study the relationship of process instance number, speedup to find the maximum acceleration process number and the number of processes when parallel efficiency is highest, which provides a scientific basis for researchers to optimize the computational program between computational resources and computation efficiency. The successful application of MPI in GMT, utilizes the computing resources fully and efficiently, improves the computational efficiency, solve the long time cost and unstable problem of Monte Carlo method in large-scale event simulations, plays an important role in the large-scale scanning calculation of the spallation target.
- ADS颗粒靶 /
- MPI /
- GMT /
- 随机数 /
- 数据传输 /
- 加速比
Abstract: For the research and design of the ADS granular-flow target concept, the Institute of Modern Physics, CAS has developed a Monte Carlo simulation software (GPU-accelerated Monte Carlo Transport program, GMT). In order to improve the computational efficiency of the GMT program, development and application of MPI in GMT were studied, to realize random distribution of the large-scale random number in the sub processes. Rapid reading and writing files were employed instead of the MPI data communication function, which greatly improves the computational efficiency. Different scale calculations were performed to study the relationship of process instance number, speedup to find the maximum acceleration process number and the number of processes when parallel efficiency is highest, which provides a scientific basis for researchers to optimize the computational program between computational resources and computation efficiency. The successful application of MPI in GMT, utilizes the computing resources fully and efficiently, improves the computational efficiency, solve the long time cost and unstable problem of Monte Carlo method in large-scale event simulations, plays an important role in the large-scale scanning calculation of the spallation target.
- ADS granular-flow target /
- MPI /
- GMT /
- random number /
- data transmission /
- speedup

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[2]	YANG Lei, ZHAN Wenlong. Science China Technological Sciences, 2015, 58: 1.
[3]	DENISE B, PELOWIT Z. MCNPXTM Users's manual. Ver-sion 2.6.0, LA-CP-07-1473. US, Los Alamos National Labo-ratory, 2008: 1.
[4]	AGOSTINELLI S, ALLISON J, AMAKO K, et al. Nucl Instr and Meth A, 2003, 506(3): 250.
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[6]	DENG Li, LI Gang. Chinese Journal of computational Physics, 2010, 27: 791. (in Chinese)(邓力, 李刚. 计算物理, 2010, 27: 791.)
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MPI在蒙特卡罗程序GMT中的应用和发展

doi: 10.11804/NuclPhysRev.34.02.204

1. 中国科学技术大学, 合肥 230026;

2. 中国科学院近代物理研究所, 兰州 730000

基金项目: 中国科学院战略性先导科技专项（XDA03030100）

作者简介:
许建亚(1988-),男,甘肃定西人,研究实习员,从事高性能计算研究：E-mail:xujianya@impcas.ac.cn

通讯作者: 杨磊,E-mail:lyang@impcas.ac.cn。

收稿日期: 2016-06-20
修回日期: 2016-08-24
刊出日期: 2017-06-20

中图分类号: TL329

关键词:

ADS颗粒靶 /

MPI /

GMT /

随机数 /

数据传输 /

加速比

摘要: 针对ADS颗粒靶概念的研究和设计，中国科学院近代物理研究所自主研发了蒙特卡罗模拟软件GMT。为了提高GMT程序的计算效率，研究了MPI在GMT中的应用和发展，实现了大规模随机数在进程中的随机分配，并采用快速读写文件的方式替代了MPI相关数据通信函数，极大地提高了计算效率。并研究了不同规模计算实例进程数、加速比、效率之间的关系，确定了最大加速进程数及并行效率最高时的进程数，为科研工作者在计算资源和计算效率之间选择最优计算方案提供了科学依据。MPI在GMT中的成功应用使计算资源得到了充分、高效的利用，极大地提高了计算效率，解决了蒙特卡罗方法中大规模事件模拟计算时间长、计算不稳定等问题，在散裂靶大规模扫描计算中发挥了重要的作用。

For the research and design of the ADS granular-flow target concept, the Institute of Modern Physics, CAS has developed a Monte Carlo simulation software (GPU-accelerated Monte Carlo Transport program, GMT). In order to improve the computational efficiency of the GMT program, development and application of MPI in GMT were studied, to realize random distribution of the large-scale random number in the sub processes. Rapid reading and writing files were employed instead of the MPI data communication function, which greatly improves the computational efficiency. Different scale calculations were performed to study the relationship of process instance number, speedup to find the maximum acceleration process number and the number of processes when parallel efficiency is highest, which provides a scientific basis for researchers to optimize the computational program between computational resources and computation efficiency. The successful application of MPI in GMT, utilizes the computing resources fully and efficiently, improves the computational efficiency, solve the long time cost and unstable problem of Monte Carlo method in large-scale event simulations, plays an important role in the large-scale scanning calculation of the spallation target.

English Abstract

Application and Development of MPI in Monte Carlo Code GMT

1. University of Science and Technology of China, Hefei 230026, China;

2. Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China

Funds: Strategic Priority Research Program of Chinese Academy of Sciences(XDA03030100)

Received Date: 2016-06-20
Rev Recd Date: 2016-08-24
Publish Date: 2017-06-20

Keywords:

Abstract: For the research and design of the ADS granular-flow target concept, the Institute of Modern Physics, CAS has developed a Monte Carlo simulation software (GPU-accelerated Monte Carlo Transport program, GMT). In order to improve the computational efficiency of the GMT program, development and application of MPI in GMT were studied, to realize random distribution of the large-scale random number in the sub processes. Rapid reading and writing files were employed instead of the MPI data communication function, which greatly improves the computational efficiency. Different scale calculations were performed to study the relationship of process instance number, speedup to find the maximum acceleration process number and the number of processes when parallel efficiency is highest, which provides a scientific basis for researchers to optimize the computational program between computational resources and computation efficiency. The successful application of MPI in GMT, utilizes the computing resources fully and efficiently, improves the computational efficiency, solve the long time cost and unstable problem of Monte Carlo method in large-scale event simulations, plays an important role in the large-scale scanning calculation of the spallation target.

引用本文: