• DocumentCode
    1918044
  • Title

    Evaluating Performance and Energy on ARM-based Clusters for High Performance Computing

  • Author

    Padoin, Edson L. ; de Oliveira, Daniel A. G. ; Velho, Pedro ; Navaux, Philippe O A

  • Author_Institution
    Inst. of Inf., Fed. Univ. of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
  • fYear
    2012
  • fDate
    10-13 Sept. 2012
  • Firstpage
    165
  • Lastpage
    172
  • Abstract
    The High-Performance Computing (HPC) community aimed for many years at increasing performance regardless to energy consumption. However, energy is limiting the scalability of next generation supercomputers. Current HPC systems already cost huge amounts of power, in the order of a few Mega Watts (MW). The future HPC systems intend to achieve 10 to 100 times more performance, but the accepted energy to power those machines must remain below 20 MW. Therefore, the scientific community is investigating ways to improve energy efficiency. This paper presents a study of the execution time, power consumption, maximum power and energy efficiency using developer boards with ARM processors. Our objective is to verify the feasibility of clusters using processors that target low power consumption. As a sub product of our research we built an unconventional cluster of Panda Boards each one featuring two ARM Cortex A9 cores. We believe that these unconventional solutions bring an alternative base to build HPC clusters that respect the limits of electric energy.
  • Keywords
    microprocessor chips; multiprocessing systems; performance evaluation; power aware computing; ARM Cortex A9 cores; ARM based clusters; HPC; MW; Mega Watts; electric energy; energy consumption; energy efficiency; evaluating performance; high performance computing; panda boards; scientific community; Benchmark testing; Clocks; Computer architecture; Energy consumption; Performance evaluation; Power demand; Program processors; ARM processors; ARM-based cluster; developer boards; energy efficiency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops (ICPPW), 2012 41st International Conference on
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1530-2016
  • Print_ISBN
    978-1-4673-2509-7
  • Type

    conf

  • DOI
    10.1109/ICPPW.2012.21
  • Filename
    6337476