SC20 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Managing Event-Oriented Workflows


Workshop:XLOOP 2020: 2nd Annual Workshop on Extreme-Scale Experiment-in-the-Loop-Computing

Authors: David Marchant (University of Copenhagen, Niels Bohr Institute)


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 interdependencies. 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 assess the feasibility of the design, which is found to be sufficient, especially in light of recent workflow requirements for dynamic looping, optional outputs and in-the-loop interactions.





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