• DocumentCode
    2522879
  • Title

    Task allocation for minimum system power in a homogenous multi-core processor

  • Author

    Ge, Yang ; Qiu, Qinru

  • Author_Institution
    Dept. of Electr. & Comput. Eng., SUNY - Binghamton Univ., Binghamton, NY, USA
  • fYear
    2010
  • fDate
    15-18 Aug. 2010
  • Firstpage
    299
  • Lastpage
    306
  • Abstract
    In this paper we address the impact of task allocation to the system power consumption of a homogenous multi-core processor with a main focus on its impact on the leakage power and fan power. Although the leakage power is determined by the average die temperature and the fan power is determined by the peak temperature, our analysis shows that the overall power can be minimized if a task allocation with minimum peak temperature is adopted together with an intelligent fan speed adjustment technique that finds the optimal tradeoff between fan power and leakage power. We further propose a multi-agent distributed task migration technique that searches for the best task allocation during runtime. By choosing only those migration requests that will result chip maximum temperature reduction, the proposed framework achieves large fan power savings as well as overall power reduction. Experimental results show that, our agent-based distributed task migration policy can save up to 37.2% fan power and 17.9% system overall power compared to the random mapping policy when the temperature constraint is tight. When the temperature constraint is loose, the overall system power is insensitive to the task allocation.
  • Keywords
    distributed processing; multi-agent systems; multiprocessing systems; power aware computing; chip maximum temperature reduction; fan power; homogenous multicore processor; intelligent fan speed adjustment technique; leakage power; multiagent distributed task migration technique; system power consumption; task allocation; Cooling; Mathematical model; Power demand; Resistance; Resource management; Temperature dependence; Temperature distribution; low power; multi-agent distributed framework; task allocation; thermal aware;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing Conference, 2010 International
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4244-7612-1
  • Type

    conf

  • DOI
    10.1109/GREENCOMP.2010.5598299
  • Filename
    5598299