• DocumentCode
    2131
  • Title

    Survey of Energy-Cognizant Scheduling Techniques

  • Author

    Zhuravlev, S. ; Saez, J.C. ; Blagodurov, Sergey ; Fedorova, Alexandra ; Prieto, M.

  • Author_Institution
    Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
  • Volume
    24
  • Issue
    7
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    1447
  • Lastpage
    1464
  • Abstract
    Execution time is no longer the only metric by which computational systems are judged. In fact, explicitly sacrificing raw performance in exchange for energy savings is becoming a common trend in environments ranging from large server farms attempting to minimize cooling costs to mobile devices trying to prolong battery life. Hardware designers, well aware of these trends, include capabilities like DVFS (to throttle core frequency) into almost all modern systems. However, hardware capabilities on their own are insufficient and must be paired with other logic to decide if, when, and by how much to apply energy-minimizing techniques while still meeting performance goals. One obvious choice is to place this logic into the OS scheduler. This choice is particularly attractive due to the relative simplicity, low cost, and low risk associated with modifying only the scheduler part of the OS. Herein we survey the vast field of research on energy-cognizant schedulers. We discuss scheduling techniques to perform energy-efficient computation. We further explore how the energy-cognizant scheduler´s role has been extended beyond simple energy minimization to also include related issues like the avoidance of negative thermal effects as well as addressing asymmetric multicore architectures.
  • Keywords
    battery management systems; cost reduction; energy conservation; multiprocessing systems; operating systems (computers); power aware computing; processor scheduling; OS scheduler; asymmetric multicore architecture; cooling cost minimisation; energy cognizant scheduling technique; energy efficient computation; energy minimization; energy saving; hardware designer; mobile device; prolong battery life; server farm; survey; Energy consumption; Hardware; Heuristic algorithms; Instruction sets; Processor scheduling; Thermal management; Survey; asymmetric multicore processors; cooperative resource sharing; power-aware scheduling; shared resource contention; thermal effects; thread level scheduling;
  • fLanguage
    English
  • Journal_Title
    Parallel and Distributed Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9219
  • Type

    jour

  • DOI
    10.1109/TPDS.2012.20
  • Filename
    6127864