loading
Papers

Research.Publish.Connect.

Paper

Authors: Ferran Badosa 1 ; Antonio Espinosa 1 ; Gonzalo Vera 2 and Ana Ripoll 1

Affiliations: 1 Universitat Autònoma de Barcelona, Spain ; 2 Center for Research in Agricultural Genomics, Spain

ISBN: 978-989-758-297-4

Keyword(s): Bioinformatics Workflows, Slowdown, Dependencies, Scheduling Policies, Backfill, Resource Management Systems.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Biomedical Signal Processing

Abstract: In this work we present the bio-backfill scheduler, a backfill scheduler for bioinformatics workflows applications running on shared, heterogeneous clusters. Backfill techniques advance low-priority jobs in cluster queues, if doing so doesn't delay higher-priority jobs. They improve the resource utilization and turnaround achieved with classical policies such as First Come First Served, Longest Job First.. When attempting to implement backfill techniques such as Firstfit or Bestfit on bioinformatics workflows, we have found several issues. Backfill requires runtime predictions, which is particularly difficult for bioinformatics applications. Their performance varies substantially depending on input datasets and the values of its many configuration parameters. Furthermore, backfill approaches are mainly intended to schedule independent, rather than dependent tasks as those forming workflows. Backfilled jobs are chosen upon its number of processors and length runtime, but not by conside ring the amount of slowdown when the Degree of Multiprogramming of the nodes is greater than 1. To tackle these issues, we developed the bio-backfill scheduler. Based on a predictor generating performance predictions of each job with multiple resources, and a resource-sharing model that minimizes slowdown, we designed a scheduling algorithm capable of backfilling bioinformatics workflows applications. Our experiments show that our proposal can improve average workflow turnaround by roughly 9\% by and resource utilization by almost 4\%, compared to popular backfill strategies such as Firstfit or BestFit. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.175.201.14

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Badosa, F.; Espinosa, A.; Vera, G. and Ripoll, A. (2018). Bio-backfill: A Scheduling Policy Enhancing the Performance of Bioinformatics Workflows in Shared Clusters.In Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS, ISBN 978-989-758-297-4, pages 148-156. DOI: 10.5220/0006812901480156

@conference{complexis18,
author={Ferran Badosa. and Antonio Espinosa. and Gonzalo Vera. and Ana Ripoll.},
title={Bio-backfill: A Scheduling Policy Enhancing the Performance of Bioinformatics Workflows in Shared Clusters},
booktitle={Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,},
year={2018},
pages={148-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006812901480156},
isbn={978-989-758-297-4},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS,
TI - Bio-backfill: A Scheduling Policy Enhancing the Performance of Bioinformatics Workflows in Shared Clusters
SN - 978-989-758-297-4
AU - Badosa, F.
AU - Espinosa, A.
AU - Vera, G.
AU - Ripoll, A.
PY - 2018
SP - 148
EP - 156
DO - 10.5220/0006812901480156

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.