• DocumentCode
    88246
  • Title

    Dynamic Power Management Technique for Multicore Based Embedded Mobile Devices

  • Author

    Young-Si Hwang ; Ki-Seok Chung

  • Author_Institution
    Dept. of Electron., Comput., & Commun. Eng., Hanyang Univ., Seoul, South Korea
  • Volume
    9
  • Issue
    3
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    1601
  • Lastpage
    1612
  • Abstract
    As the proliferation of ubiquitous computing environments becomes a reality, the need for high speed data processing and intelligent system management increases rapidly. In particular, the need for low-power designs and power-aware system management is getting stronger. While multicore systems are deployed in many embedded system areas, an effective power management technique for multicores is not available yet. In this paper, we propose a novel power management technique based on a parallel programming model. OpenMP is a well-known programming paradigm for shared memory multicore systems. OpenMP is based on library routines for parallel processing. By identifying the invoked library routines, how many cores will be adequate for a certain application can be determined, and the number of necessary cores for a given task can be determined during run-time. By turning off unnecessary cores, we can reduce power consumption. We implemented this method by adding capabilities in an OpenMP-compliant compiler and conducted experiments with various benchmarks. We were able to reduce the power consumption by 18% on average compared to other conventional power management methods.
  • Keywords
    embedded systems; mobile computing; parallel processing; power aware computing; program compilers; shared memory systems; OpenMP-compliant compiler; dynamic power management technique; embedded system; high speed data processing; low-power designs; multicore based embedded mobile devices; parallel processing; power consumption; power-aware system management; shared memory multicore systems; ubiquitous computing environments; Benchmark testing; Libraries; Multicore processing; Parallel programming; Power demand; Program processors; Runtime; Dynamic power management; low-power design; multicore; open multiprocessing (OpenMP);
  • fLanguage
    English
  • Journal_Title
    Industrial Informatics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1551-3203
  • Type

    jour

  • DOI
    10.1109/TII.2012.2232299
  • Filename
    6376178