• DocumentCode
    2177519
  • Title

    Predictive models for multimedia applications power consumption based on use-case and OS level analysis

  • Author

    Bellasi, Patrick ; Fornaciari, William ; Siorpaes, David

  • Author_Institution
    Dipt. di Elettron. e Inf., Politec. di Milano, Milan
  • fYear
    2009
  • fDate
    20-24 April 2009
  • Firstpage
    1446
  • Lastpage
    1451
  • Abstract
    Power management at any abstraction level is a key issue for many mobile multimedia and embedded applications. In this paper a design workflow to generate system-level power models will be presented, tailored to support quantitative run-time power optimization policies to be implemented within an operating system. The approach we followed to derive power models is strongly use-case oriented. Starting from a comprehensive general and accurate model of a representative architecture for embedded applications (including a multi core MPSoC, accelerators, interfaces and peripherals), a methodology to derive compact models is presented, based upon the distinctive characteristics of the selected use cases. The methodology to generate such model, whose exploitation is foreseen within a power manager working at the OS level, is the focus of the paper. The value and accuracy of the approach is quantitatively and statistically justified through extensive experiments carried out on a development board designed for multimedia applications.
  • Keywords
    multimedia communication; telecommunication power supplies; multimedia applications power consumption; power management; predictive models; system-level power models; Design optimization; Energy consumption; Energy management; Operating systems; Power generation; Power system management; Power system modeling; Predictive models; Proposals; Runtime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation & Test in Europe Conference & Exhibition, 2009. DATE '09.
  • Conference_Location
    Nice
  • ISSN
    1530-1591
  • Print_ISBN
    978-1-4244-3781-8
  • Type

    conf

  • DOI
    10.1109/DATE.2009.5090891
  • Filename
    5090891