Distributed workflows for modeling experimental data

Vickie E. Lynch, Jose Borreguero Calvo, Ewa Deelman, Rafael Ferreira Da Silva, Monojoy Goswami, Yawei Hui, Eric Lingerfelt, Jeffrey S. Vetter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Modeling helps explain the fundamental physics hidden behind experimental data. In the case of material modeling, running one simulation rarely results in output that reproduces the experimental data. Often one or more of the force field parameters are not precisely known and must be optimized for the output to match that of the experiment. Since the simulations require high performance computing (HPC) resources and there are usually many simulations to run, a workflow is very useful to prevent errors and assure that the simulations are identical except for the parameters that need to be varied. The use of HPC implies distributed workflows, but the optimization and steps to compare the simulation results and experimental data are done on a local workstation. We will present results from force field refinement of data collected at the Spallation Neutron Source using Kepler, Pegasus, and BEAM workflows and discuss what we have learned from using these workflows.

Original languageEnglish
Title of host publication2017 IEEE High Performance Extreme Computing Conference, HPEC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538634721
DOIs
StatePublished - Oct 30 2017
Event2017 IEEE High Performance Extreme Computing Conference, HPEC 2017 - Waltham, United States
Duration: Sep 12 2017Sep 14 2017

Publication series

Name2017 IEEE High Performance Extreme Computing Conference, HPEC 2017

Conference

Conference2017 IEEE High Performance Extreme Computing Conference, HPEC 2017
Country/TerritoryUnited States
CityWaltham
Period09/12/1709/14/17

Keywords

  • experiments
  • modeling
  • simulations
  • workflows

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