• DocumentCode
    1919945
  • Title

    Poster: Statistical Power and Energy Modeling of Multi-GPU Kernels

  • Author

    Ghosh, Sudip ; Chandrasekaran, S. ; Chapman, Barbara M.

  • Author_Institution
    Comput. Sci. Dept., Univ. of Houston, Houston, TX, USA
  • fYear
    2012
  • fDate
    10-16 Nov. 2012
  • Firstpage
    1516
  • Lastpage
    1516
  • Abstract
    To improve the energy efficiency of parallel applications on GPGPUs, a better understanding of the energy behavior of various applications is mandatory. In this study we employ statistical methods to model power and energy consumption of some common optimized high performance kernels (DGEMM, FFT, PRNG and FD stencils) on a multi-GPU platform.
  • Keywords
    energy conservation; graphics processing units; power aware computing; statistical analysis; GPGPU; energy consumption; energy efficiency; energy modeling; multiGPU kernels; optimized high performance kernels; parallel applications; statistical methods; statistical power; GPGPU; Power; Statistical Modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    978-1-4673-6218-4
  • Type

    conf

  • DOI
    10.1109/SC.Companion.2012.298
  • Filename
    6496081