Science automation in practice: Performance data farming in workflows

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

2 Scopus citations

Abstract

This paper describes an approach to conduct large-scale parameter studies, where each data point in the study requires the execution of a whole scientific workflow. We show how a parameter studies system can be integrated with a workflow management system to seamlessly execute a large number of workflows, each with different input parameter values using large-scale computing infrastructure. The work is motivated by a need to collect performance-related data to conduct a sensitivity analysis in the context of relation between workflow input parameters and the performance of tasks in the workflow developed for the Spallation Neutron Source facility at the Oak Ridge National Laboratory.

Original languageEnglish
Title of host publication2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013142
DOIs
StatePublished - Nov 3 2016
Event21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016 - Berlin, Germany
Duration: Sep 6 2016Sep 9 2016

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2016-November
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

Conference21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016
Country/TerritoryGermany
CityBerlin
Period09/6/1609/9/16

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