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Job Scheduling in a Computational Cluster with Multicore Processors

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Advanced Computational Methods for Knowledge Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 453))

Abstract

In this paper, we investigate a job scheduling problem in a heterogeneous computing cluster built from servers with multicore processors. Dynamic Power Management technique is applied, where the delay to bring a server from the sleep to the active state is taken into account. Numerical results show that the computing resources are utilized more efficiently if multi jobs are executed in parallel. Furthermore, scheduling policy should investigate machine parameters at core-level to achieve the best efficiency.

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Authors and Affiliations

  1. Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary

    Tran Thi Xuan & Tien Van Do

Authors
  1. Tran Thi Xuan
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  2. Tien Van Do
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Corresponding author

Correspondence to Tien Van Do .

Editor information

Editors and Affiliations

  1. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Thanh Binh Nguyen

  2. Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary

    Tien van Do

  3. Laboratory of Theoretical and Applied Computer Science (LITA), UFR MIM, University of Lorraine, Ile du Saulcy, Metz, France

    Hoai An Le Thi

  4. Institute of Informatics, Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

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Xuan, T.T., Do, T.V. (2016). Job Scheduling in a Computational Cluster with Multicore Processors. In: Nguyen, T.B., van Do, T., An Le Thi, H., Nguyen, N.T. (eds) Advanced Computational Methods for Knowledge Engineering. Advances in Intelligent Systems and Computing, vol 453. Springer, Cham. https://doi.org/10.1007/978-3-319-38884-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-38884-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38883-0

  • Online ISBN: 978-3-319-38884-7

  • eBook Packages: EngineeringEngineering (R0)

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