• DocumentCode
    1926387
  • Title

    Topics on measuring real power usage on high performance computing platforms

  • Author

    Laros, James H., III ; Pedretti, Kevin T. ; Kelly, Suzanne M. ; Vandyke, John P. ; Ferreira, Kurt B. ; Vaughan, Courtenay T. ; Swan, Mark

  • fYear
    2009
  • fDate
    Aug. 31 2009-Sept. 4 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Power has recently been recognized as one of the major obstacles in fielding a Peta-FLOPs class system. To reach Exa-FLOPs, the challenge will certainly be compounded. In this paper we will discuss a number of High Performance Computing power related topics. We first describe our implementation of a scalable power measurement framework that has enabled us to examine real power use (current draw). [Using this framework, samples were obtained at a per-node (socket) granularity, at frequencies of up to 100 samples per second.] Additionally, we describe how we applied this capability to implement power conserving measures on our Catamount Light Weight Kernel, where we achieved an 80% improvement. This ability has enabled us to quantify the amount of energy used by applications and to contrast application energy use between a Light Weight and General Purpose operating system. Finally, we show application energy use increases proportionally with the increase in run-time due to operating system noise. Areas of future interest will also be discussed.
  • Keywords
    operating system kernels; power aware computing; Exa-FLOPs class system; Peta-FLOPs class system; catamount light weight kernel; general purpose operating system; high performance computing platforms; high performance computing power; light weight operating system; power conserving measure; real power usage; scalable power measurement framework; socket granularity; Current measurement; Frequency; Hardware; High performance computing; Laboratories; Linux; Operating systems; Power measurement; Sockets; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing and Workshops, 2009. CLUSTER '09. IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • ISSN
    1552-5244
  • Print_ISBN
    978-1-4244-5011-4
  • Electronic_ISBN
    1552-5244
  • Type

    conf

  • DOI
    10.1109/CLUSTR.2009.5289179
  • Filename
    5289179