• DocumentCode
    611101
  • Title

    Heterogeneity: The Key to Achieve Power-Proportional Computing

  • Author

    da Costa, Geraldo

  • Author_Institution
    IRIT, Univ. de Toulouse, Toulouse, France
  • fYear
    2013
  • fDate
    13-16 May 2013
  • Firstpage
    656
  • Lastpage
    662
  • Abstract
    The Smart 2020 report on low carbon economy in the information age shows that 2% of the global CO2 footprint will come from ICT in 2020. Out of these, 18% will be caused by data-centers, while 45% will come from personal computers. Classical research to reduce this footprint usually focuses on new consolidation techniques for global data-centers. In reality, personal computers and private computing infrastructures are here to stay. They are subject to irregular workload, and are usually largely under-loaded. Most of these computers waste tremendous amount of energy as nearly half of their maximum power consumption comes from simply being switched on. The ideal situation would be to use proportional computers that use nearly 0W when lightly loaded. This article shows the gains of using a perfectly proportional hardware on different type of data-centers: 50% gains for the servers used during 98 World Cup, 20% to the already optimized Google servers. Gains would attain up to 80% for personal computers. As such perfect hardware still does not exist, a real platform composed of Intel I7, Intel Atom and Raspberry Pi is evaluated. Using this infrastructure, gains are of 20% for the World Cup data-center, 5% for Google data-centers and up to 60% for personal computers.
  • Keywords
    computer centres; energy conservation; environmental economics; microcomputers; power aware computing; power consumption; Google data centers; ICT; Intel Atom; Intel I7; Raspberry Pi; World Cup data center; carbon economy; consolidation techniques; energy wastage; global carbon dioxide footprint; global data centers; heterogeneity; maximum power consumption; optimized Google servers; personal computers; power-proportional computing; private computing infrastructures; Google; Hardware; Microcomputers; Power demand; Program processors; Servers; Switches; Data-centers; Energy efficiency; Heterogeneous architectures; Large scale; Power proportional;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on
  • Conference_Location
    Delft
  • Print_ISBN
    978-1-4673-6465-2
  • Type

    conf

  • DOI
    10.1109/CCGrid.2013.90
  • Filename
    6546153