research-article

Enabling workflow repeatability with virtualization support

Authors:

Claris Castillo,

Charles Schmitt,

Anirban Mandal,

Ilya BaldinAuthors Info & Claims

WORKS '15: Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science

Article No.: 8, Pages 1 - 10

https://doi.org/10.1145/2822332.2822340

Published: 15 November 2015 Publication History

Abstract

The value of workflows to the scientific community spans over time and space. Not only results but also performance and resource consumption of a workflow need to be replayed over time and in varying environments. Achieving such repeatability in practice is challenging due to changes in software and infrastructure over time. In this work, we introduce a new abstraction that builds on the concept of virtual appliance to enable workflow repeatability. We have also developed a novel architecture to leverage this abstraction and realized it into a system implementation that supports a popular workflow management system and builds on a federated in-production environment. We demonstrate the effectiveness of our approach by examining various aspects of workflow repeatability. Our results show that workflows can be replayed with 2% fidelity when considering their walltime as performance metric.

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Cited By

Qasha RWen ZCała JWatson P(2022)Sharing and performance optimization of reproducible workflows in the cloudFuture Generation Computer Systems10.1016/j.future.2019.03.04598:C(487-502)Online publication date: 21-Apr-2022
https://dl.acm.org/doi/10.1016/j.future.2019.03.045
Weder BBreitenbücher UKépes KLeymann FZimmermann M(2020)Deployable Self-contained Workflow ModelsService-Oriented and Cloud Computing10.1007/978-3-030-44769-4_7(85-96)Online publication date: 27-Mar-2020
https://doi.org/10.1007/978-3-030-44769-4_7
Qasha RCala JWatson P(2016)A framework for scientific workflow reproducibility in the cloud2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870888(81-90)Online publication date: Oct-2016
https://doi.org/10.1109/eScience.2016.7870888

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cover image ACM Conferences

WORKS '15: Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science

November 2015

98 pages

ISBN:9781450339896

DOI:10.1145/2822332

Conference Chairs:
Johan Montagnat
CNRS, France
,
Ian Taylor
Cardiff University, UK

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGHPC: ACM Special Interest Group on High Performance Computing, Special Interest Group on High Performance Computing
SIGARCH: ACM Special Interest Group on Computer Architecture
IEEE-CS\DATC: IEEE Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 November 2015

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National Science Fundation

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SC15

Sponsor:

SIGHPC
SIGARCH
IEEE-CS\DATC

SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis

November 15, 2015

Texas, Austin

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WORKS '15 Paper Acceptance Rate 9 of 13 submissions, 69%;

Overall Acceptance Rate 30 of 54 submissions, 56%

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Cited By

Qasha RWen ZCała JWatson P(2022)Sharing and performance optimization of reproducible workflows in the cloudFuture Generation Computer Systems10.1016/j.future.2019.03.04598:C(487-502)Online publication date: 21-Apr-2022
https://dl.acm.org/doi/10.1016/j.future.2019.03.045
Weder BBreitenbücher UKépes KLeymann FZimmermann M(2020)Deployable Self-contained Workflow ModelsService-Oriented and Cloud Computing10.1007/978-3-030-44769-4_7(85-96)Online publication date: 27-Mar-2020
https://doi.org/10.1007/978-3-030-44769-4_7
Qasha RCala JWatson P(2016)A framework for scientific workflow reproducibility in the cloud2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870888(81-90)Online publication date: Oct-2016
https://doi.org/10.1109/eScience.2016.7870888

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