Researchers’ Work from University of Michigan Focuses on Risk Management (Tutorial: Parallel Computing of Simulation Models for Risk Analysis)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Current study results on Risk Management have been published. According to news reporting originating in Ann Arbor, Michigan, by VerticalNews journalists, research stated, "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."

The news reporters obtained a quote from the research from the University of Michigan, "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."

According to the news reporters, the research concluded: "Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix."

For more information on this research see: Tutorial: Parallel Computing of Simulation Models for Risk Analysis. Risk Analysis, 2016;36(10):1844-1854. Risk Analysis can be contacted at: Wiley-Blackwell, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; Risk Analysis - onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6924)

Our news correspondents report that additional information may be obtained by contacting A.C. Reilly, University of Michigan, Ind & Operat Res, Ann Arbor, MI 48109, United States. Additional authors for this research include A. Staid, M. Gao and S.D. Guikema.

Keywords for this news article include: Ann Arbor, Michigan, United States, North and Central America, Risk Management, University of Michigan.

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