Custom execution environments with containers in pegasus-enabled scientific workflows

Karan Vahi, Michael Zink, Mats Rynge, George Papadimitriou, Duncan Brown, Rajiv Mayani, Rafael Ferreira Da Silva, Ewa Deelman, Anirban Mandal, Eric Lyons

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

7 Scopus citations

Abstract

Science reproducibility is a cornerstone feature in scientific workflows. In most cases, this has been implemented as a way to exactly reproduce the computational steps taken to reach the final results. While these steps are often completely described, including the input parameters, datasets, and codes, the environment in which these steps are executed is only described at a higher level with endpoints and operating system name and versions. Though this may be sufficient for reproducibility in the short term, systems evolve and are replaced over time, breaking the underlying workflow reproducibility. A natural solution to this problem is containers, as they are well defined, have a lifetime independent of the underlying system, and can be user-controlled so that they can provide custom environments if needed. This paper highlights some unique challenges that may arise when using containers in distributed scientific workflows. Further, this paper explores how the Pegasus Workflow Management System implements container support to address such challenges.

Original languageEnglish
Title of host publicationProceedings - IEEE 15th International Conference on eScience, eScience 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages281-290
Number of pages10
ISBN (Electronic)9781728124513
DOIs
StatePublished - Sep 2019
Externally publishedYes
Event15th IEEE International Conference on eScience, eScience 2019 - San Diego, United States
Duration: Sep 24 2019Sep 27 2019

Publication series

NameProceedings - IEEE 15th International Conference on eScience, eScience 2019

Conference

Conference15th IEEE International Conference on eScience, eScience 2019
Country/TerritoryUnited States
CitySan Diego
Period09/24/1909/27/19

Funding

ACKNOWLEDGMENTS This work is funded by NSF contract #1664162, “SI2-SSI: Pegasus: Automating Compute and Data Intensive Science”; and NSF contract #1826997, “CC* Integration: Delivering a Dynamic Network-Centric Platform for Data-Driven Science (DyNamo)”. Development of containerization in PyCBC was supported by NSF contract #1443047, “CIF21 DIBBs: Domain-Aware Management of Heterogeneous Workflows: Active Data Management for Gravitational-Wave Science Workflows.” DAB was supported in part by NSF contract #1748958 to the Kavli Institute for Theoretical Physics.

FundersFunder number
National Science Foundation1748958, 1664162, 1443047, 1826997
Kavli Institute for Theoretical Physics, University of California, Santa Barbara

    Keywords

    • Containers
    • Distributed computing
    • Docker
    • Pegasus
    • Reproducibility
    • Scientific workflows
    • Shifter
    • Singularity

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