• DocumentCode
    1606990
  • Title

    Energy and performance tradeoffs for matrix multiplication on multicore machines

  • Author

    Wang, Zhe ; Tan, Hengxing ; Ranka, Sanjay

  • Author_Institution
    Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we propose a general methodology for energy estimation of bus-based multi-core processors assuming that DVS can be used for both buses and cores. Our formulation can provide tradeoffs between DVS setting for buses and cores. We examine this methodology using various parallel matrix multiplication algorithms that are suitable for shared memory multicore machines with L1 and L2 caches. Our simulation results show that the simultaneously changing the voltage of buses along with cores can result in 10 - 20% reduction in the overall energy requirements as compared to only changing the core voltages. This is under the assumption that sufficient slack is available for DVS to be able to work at lower voltages to save energy. The methods proposed in this paper demonstrate the usefulness of multiple element optimization in multicore architectures. The experiments show that a good understanding of the overall tradeoffs between the effect of these elements in the overall performance and energy requirements can lead to improved results in the energy requirements.
  • Keywords
    energy conservation; matrix multiplication; memory architecture; multiprocessing systems; power aware computing; system buses; DVS; L1 cache; L2 cache; bus voltage; bus-based multicore processors; core voltage; dynamic voltage scaling; energy estimation; energy requirement reduction; energy tradeoff; multicore architectures; multiple element optimization; parallel matrix multiplication algorithms; performance requirements; performance tradeoff; shared memory multicore machines; Clocks; Energy consumption; Memory management; Multicore processing; Partitioning algorithms; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing Conference (IGCC), 2012 International
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4673-2155-6
  • Electronic_ISBN
    978-1-4673-2153-2
  • Type

    conf

  • DOI
    10.1109/IGCC.2012.6322295
  • Filename
    6322295