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Tutorial: Parallel Computing of Simulation Models for Risk Analysis

机译:教程:用于风险分析的仿真模型的并行计算

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摘要

Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix.
机译:仿真模型被广泛用于风险分析中,以研究不确定性对复杂问题感兴趣的结果的影响。通常,这些模型计算复杂且运行耗时。后一点可能与时间敏感性评估不一致,或者可能会限制所考虑的参数数量。在本文中,我们提供了一个入门教程,着重于并行化仿真代码以更好地利用现代计算硬件,使风险分析人员可以更好地利用基于仿真的方法来量化实践中的不确定性。本文主要针对使用模拟方法但尚未利用并行化来减轻这些模型的计算负担的风险分析师。讨论的重点是令人尴尬的并行计算机代码和软件考虑因素的概念方面。使用MATLAB和R语言显示了两个互补的示例。有关硬件注意事项的简短讨论位于附录中。

著录项

  • 来源
    《Risk analysis》 |2016年第10期|1844-1854|共11页
  • 作者单位

    Univ Michigan, Ind & Operat Res, 1205 Beal Ave, Ann Arbor, MI 48109 USA;

    Sandia Natl Labs, Discrete Math & Optimizat, POB 5800, Albuquerque, NM 87185 USA;

    SolarCity, San Mateo, CA USA;

    Univ Michigan, Ind & Operat Res, 1205 Beal Ave, Ann Arbor, MI 48109 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Parallel computing; risk analysis;

    机译:并行计算;风险分析;

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