• DocumentCode
    655086
  • Title

    Comparing the Performance and Power Usage of GPU and ARM Clusters for Map-Reduce

  • Author

    Delplace, Vivian ; Manneback, Pierre ; Pinel, Frederic ; Varrette, Sebastien ; Bouvry, Pascal

  • Author_Institution
    Fac. of Eng., Univ. of Mons, Mons, Belgium
  • fYear
    2013
  • fDate
    Sept. 30 2013-Oct. 2 2013
  • Firstpage
    199
  • Lastpage
    200
  • Abstract
    This paper compares two parallel architectures, the GPU and the integrated ARM cluster, for the execution of map-reduce applications. The comparison targets performance and power usage. The increasing importance of energy efficiency, especially for large distributed systems - such as frequently used for map-reduce - motivates the comparison of alternative parallel architectures. Because the different hardware platforms require specific map-reduce implementations, we selected two different implementations and showed that GPU provides a better performance per watt than ARM cluster, but by less than an order of magnitude. These results indicate the great potential of ARM clusters, given the differences in hardware and software between the alternatives.
  • Keywords
    distributed processing; graphics processing units; parallel architectures; performance evaluation; power aware computing; ARM clusters; GPU; Map-Reduce; distributed systems; energy efficiency; integrated ARM cluster; parallel architectures; performance; power usage; Benchmark testing; Computer architecture; Graphics processing units; Hardware; Measurement; ARM Cortex A9; Energy-effiency; GPU; HPC; MapReduce; Performance evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Green Computing (CGC), 2013 Third International Conference on
  • Conference_Location
    Karlsruhe
  • Type

    conf

  • DOI
    10.1109/CGC.2013.38
  • Filename
    6686030