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Modeling and Optimizing the Power Performance of Large Matrices Multiplication on Multi-core and GPU Platform with CUDA

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Parallel Processing and Applied Mathematics (PPAM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6067))

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Abstract

The power efficiency of large-scale computing on multiprocessing systems is an important issue that interrelated to both of the hardware architectures and the software methodologies. Aiming to design power-efficient high performance program, we have measured the power consumption of large matrices multiplication on multi-core and GPU platform. Based on the obtained power characteristic values of each computing component, we abstract the energy estimations by incorporating physical power constrains from the hardware devices and analysis of the program execution behaviors. We optimize the matrices multiplication algorithm in order to improve its power performance, and the efficiency promotion has been finally validated by measuring the program execution.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan, 113-0033

    Da Qi Ren

  2. JST, CREST, Japan

    Reiji Suda

Authors
  1. Da Qi Ren
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  2. Reiji Suda
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Editor information

Editors and Affiliations

  1. Institute of Computational and Information Sciences, Czestochowa University of Technology,  

    Roman Wyrzykowski

  2. Department of Electrical Engineering and Computer Science, University of Tennessee, TN 37996-3450, Knoxville, USA

    Jack Dongarra

  3. Institute of Computer and Information Science, Czestochowa University of Technology, Dabrowskiego 73, PL-42-200, Czestochowa, Poland

    Konrad Karczewski

  4. Department of Informatics and Mathematical Modeling, Technical University of Denmark, Richard Petersens Plads, Building 321, 2800, Kongens Lyngby, Denmark

    Jerzy Wasniewski

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© 2010 Springer-Verlag Berlin Heidelberg

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Ren, D.Q., Suda, R. (2010). Modeling and Optimizing the Power Performance of Large Matrices Multiplication on Multi-core and GPU Platform with CUDA. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2009. Lecture Notes in Computer Science, vol 6067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14390-8_44

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  • DOI: https://doi.org/10.1007/978-3-642-14390-8_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14389-2

  • Online ISBN: 978-3-642-14390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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