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Monte Carlo simulation with the GATE software using grid computing

Published: 23 June 2008 Publication History

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.

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Cited By

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  • (2021)Machine Intelligence of Pi From Geometrical Figures With Variable Parameters Using SCILabMethodologies and Applications of Computational Statistics for Machine Intelligence10.4018/978-1-7998-7701-1.ch003(38-63)Online publication date: 2021
  • (2010)Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEEJournal of Grid Computing10.1007/s10723-010-9153-08:2(241-259)Online publication date: 23-Mar-2010

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Published In

cover image ACM Conferences
NOTERE '08: Proceedings of the 8th international conference on New technologies in distributed systems
June 2008
399 pages
ISBN:9781595939371
DOI:10.1145/1416729
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • Lyon 1 University
  • SIGAPP: ACM Special Interest Group on Applied Computing
  • Mairie de Villeurbanne
  • Conseil Général du Rhône
  • INSA Lyon: Institut National des Sciences Appliquées de Lyon
  • Conseil Régional Rhône-Alpes
  • Mutuelle d'assurance MAIF
  • I.U.T.A LYON 1: Institute of Technology Lyon 1
  • Ministère de l'Enseignement Supérieur et de la Recherche
  • Lyon 2 University
  • ISTASE: High-Level Engineering School in Telecommunication
  • France Telecom
  • LIRIS: Lyon Research Center for Images and Intelligent Information Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 June 2008

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Author Tags

  1. GATE simulation
  2. Monte Carlo
  3. grid computing

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Cited By

View all
  • (2021)Machine Intelligence of Pi From Geometrical Figures With Variable Parameters Using SCILabMethodologies and Applications of Computational Statistics for Machine Intelligence10.4018/978-1-7998-7701-1.ch003(38-63)Online publication date: 2021
  • (2010)Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEEJournal of Grid Computing10.1007/s10723-010-9153-08:2(241-259)Online publication date: 23-Mar-2010

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