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Load Balancing for CPU-GPU Coupling in Computational Fluid Dynamics

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Book cover Parallel Processing and Applied Mathematics (PPAM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10777))

Abstract

This paper investigates static load balancing models for CPU-GPU coupling from a computational fluid dynamics perspective. While able to generate a benefit, traditional load balancing models are found to be too inaccurate to predict the runtime of a preconditioned conjugate gradient solver. Hence, an expanded model is derived that accounts for the multi-step nature of the solver, i.e. several communication barriers per iteration. It is able to predict the runtime to a margin of 5%, rendering CPU-GPU coupling better predictable so that load balancing can be improved substantially.

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Acknowledgements

This work is supported in part by the German Research Foundation (DFG) within the Cluster of Excellence “Center for Advancing Electronics Dresden” (cfaed). Computing time was provided by ZIH Dresden. The authors would like to thank Professor Karsten Eppler for advise on the optimization problem.

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Authors and Affiliations

  1. Institute of Fluid Mechanics, TU Dresden, Dresden, Germany

    Immo Huismann, Jörg Stiller & Jochen Fröhlich

  2. Center for Information Services and High Performance Computing, TU Dresden, Dresden, Germany

    Matthias Lieber

  3. Center for Advancing Electronics Dresden (cfaed), Dresden, Germany

    Immo Huismann, Matthias Lieber, Jörg Stiller & Jochen Fröhlich

Authors
  1. Immo Huismann
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  2. Matthias Lieber
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  3. Jörg Stiller
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  4. Jochen Fröhlich
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Corresponding author

Correspondence to Immo Huismann .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  3. University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  4. Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

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Huismann, I., Lieber, M., Stiller, J., Fröhlich, J. (2018). Load Balancing for CPU-GPU Coupling in Computational Fluid Dynamics. In: Wyrzykowski, R., Dongarra, J., Deelman, E., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science(), vol 10777. Springer, Cham. https://doi.org/10.1007/978-3-319-78024-5_30

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  • DOI: https://doi.org/10.1007/978-3-319-78024-5_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78023-8

  • Online ISBN: 978-3-319-78024-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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