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Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372)

Authors: Vincent Heuveline, Michael Schick, Clayton Webster, and Peter Zaspel

Published in: Dagstuhl Reports, Volume 6, Issue 9 (2017)

Abstract

High performance computing is a key technology to solve large-scale real-world simulation problems on parallel computers. Simulations for a fixed, deterministic set of parameters are current state of the art. However, there is a growing demand in methods to appropriately cope with uncertainties in those input parameters. This is addressed in the developing research field of uncertainty quantification. Here, Monte-Carlo methods are easy to parallelize and thus fit well for parallel computing. However, their weak approximation capabilities lead to inaccurate results. The Dagstuhl Seminar 16372 "Uncertainty Quantification and High Performance Computing" brought together experts in the fields of uncertainty quantification and high performance computing. Discussions on the latest numerical techniques beyond pure Monte-Carlo and with strong approximation capabilities were fostered. This has been put in context of real-world problems on parallel computers.

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Vincent Heuveline, Michael Schick, Clayton Webster, and Peter Zaspel. Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372). In Dagstuhl Reports, Volume 6, Issue 9, pp. 59-73, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{heuveline_et_al:DagRep.6.9.59,
  author =	{Heuveline, Vincent and Schick, Michael and Webster, Clayton and Zaspel, Peter},
  title =	{{Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372)}},
  pages =	{59--73},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{6},
  number =	{9},
  editor =	{Heuveline, Vincent and Schick, Michael and Webster, Clayton and Zaspel, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.9.59},
  URN =		{urn:nbn:de:0030-drops-69158},
  doi =		{10.4230/DagRep.6.9.59},
  annote =	{Keywords: high performance computing, parallelization, stochastic modeling, uncertainty quantification}
}

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Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372)

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