Monte Carlo simulation with the GATE software using grid computing

R. Reuillon, D. Hill, C. Gouinaud, Z. E. Bitar, V. Breton, I. Buvat
{"title":"Monte Carlo simulation with the GATE software using grid computing","authors":"R. Reuillon, D. Hill, C. Gouinaud, Z. E. Bitar, V. Breton, I. Buvat","doi":"10.1145/1416729.1416762","DOIUrl":null,"url":null,"abstract":"Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the \"Multiple Replications In Parallel\" approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-sciencE), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses.","PeriodicalId":321308,"journal":{"name":"NOuvelles TEchnologies de la REpartition","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NOuvelles TEchnologies de la REpartition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1416729.1416762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the "Multiple Replications In Parallel" approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-sciencE), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses.
蒙特卡罗模拟用GATE软件进行网格计算
蒙特卡罗模拟需要多次复制才能获得良好的统计结果,可以使用“多重并行复制”方法轻松地并行执行。然而,在生成伪随机数并行流时必须采取一些预防措施。在本文中,我们介绍了用GATE软件使用局部集群和网格计算进行蒙特卡罗模拟的分布。我们在这个大型医疗应用中获得了非常令人信服的结果,这要归功于EGEE网格(电子科学使能网格),在一周内实现了在一台计算机上可能需要3年以上处理的计算。这项工作的完成要归功于一个名为DistMe的通用面向对象工具箱,我们设计了它来自动实现蒙特卡罗模拟的这种并行化。这个用Java编写的工具箱可以在SourceForge上免费获得,它有助于确保伪随机数流的严格分布。它基于对随机数生成器状态的文档XML格式的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信