• DocumentCode
    2850324
  • Title

    Assignment Algorithm for Energy Minimization on Parallel Machines

  • Author

    Kang, Jaeyeon ; Ranka, Sanjay

  • Author_Institution
    Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
  • fYear
    2009
  • fDate
    22-25 Sept. 2009
  • Firstpage
    484
  • Lastpage
    491
  • Abstract
    Energy consumption is a critical issue in parallel and distributed systems. Energy-efficient scheduling of directed acyclic graph (DAG) based workflows on dynamic voltage scaling (DVS) enabled systems consists of two phases: assignment of tasks and slack allocation. Most current research on scheduling for energy minimization of DAGs tries to minimize energy by effective slack allocation for a given assignment. The assignment itself does not take energy profiles of tasks into account. In this paper, we show that incorporating DVS based energy profiles of tasks during the assignment phase can lead to significantly lower overall energy requirements while requiring lower computational time.
  • Keywords
    directed graphs; energy consumption; minimisation; parallel machines; power aware computing; processor scheduling; resource allocation; assignment algorithm; directed acyclic graph; distributed systems; dynamic voltage scaling enabled systems; energy consumption; energy minimization; energy-efficient scheduling; parallel machines; parallel systems; slack allocation; task assignment; Dynamic scheduling; Dynamic voltage scaling; Energy consumption; Energy efficiency; Genetic algorithms; Minimization methods; Parallel machines; Processor scheduling; Real time systems; Voltage control; dynamic voltage scaling; energy-efficient scheduling; parallel and distributed systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops, 2009. ICPPW '09. International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1530-2016
  • Print_ISBN
    978-1-4244-4923-1
  • Electronic_ISBN
    1530-2016
  • Type

    conf

  • DOI
    10.1109/ICPPW.2009.86
  • Filename
    5365346