Managing Event Oriented Workflows

David Marchant, Rasmus Munk, Elise Otterlei Brenne, Brian Vinter

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper introduces an event-driven solution for modern scientific workflows. This novel approach enables truly dynamic workflows by splitting them into their constituent parts, defined using combinations of Patterns and Recipes, and lacking any meaningful inter-dependencies. The theory behind this system is set out, and an example workflow is presented. A python package mig_meow, which implements this workflow system is also shown and explained. The use cases of various user groups are considered to asses the feasibility of the design, and it is found to be sufficient, especially in light of recent workflow requirements for dynamic looping, optional outputs and in-the-loop interactions.
Original languageEnglish
Title of host publication2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP)
PublisherIEEE
Publication date2020
Pages23-28
ISBN (Electronic)978-0-7381-1072-1
DOIs
Publication statusPublished - 2020
EventXLOOP 2020 : 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing - , United States
Duration: 12 Nov 202012 Nov 2020
Conference number: 2
https://wordpress.cels.anl.gov/xloop-2020

Conference

ConferenceXLOOP 2020 : 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing
Number2
Country/TerritoryUnited States
Period12/11/202012/11/2020
Internet address

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