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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 117–127Cite as

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Towards Scheduling Evolving Applications

Towards Scheduling Evolving Applications

  • Cristian Klein30 &
  • Christian Pérez30 
  • Conference paper
  • 1315 Accesses

  • 1 Citations

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7155)

Abstract

Most high-performance computing resource managers only allow applications to request a static allocation of resources. However, evolving applications have resource requirements which change (evolve) during their execution. Currently, such applications are forced to make an allocation based on their peak resource requirements, which leads to an inefficient resource usage. This paper studies whether it makes sense for resource managers to support evolving applications. It focuses on scheduling fully-predictably evolving applications on homogeneous resources, for which it proposes several algorithms and evaluates them based on simulations. Results show that resource usage and application response time can be significantly improved with short scheduling times.

Keywords

  • Completion Time
  • Schedule Algorithm
  • Resource Usage
  • Resource Requirement
  • Resource Management System

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work was supported by the French ANR COOP project, no ANR-09-COSI-001.

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Author information

Authors and Affiliations

  1. INRIA/LIP, ENS de Lyon, France

    Cristian Klein & Christian Pérez

Authors
  1. Cristian Klein
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  2. Christian Pérez
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, USA

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TU München, Boltzmannstr. 3, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Oak Ridge National Laboratory, Computer Science and Mathematics Division, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austrial

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Klein, C., Pérez, C. (2012). Towards Scheduling Evolving Applications. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29737-3_15

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  • DOI: https://doi.org/10.1007/978-3-642-29737-3_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29736-6

  • Online ISBN: 978-3-642-29737-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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