IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v331y2023i2d10.1007_s10479-022-04830-0.html
   My bibliography  Save this article

Three-level modeling of a speed-scaling supercomputer

Author

Listed:
  • Alexander Rumyantsev

    (Karelian Research Center of RAS
    Petrozavodsk State University)

  • Robert Basmadjian

    (TU Clausthal)

  • Sergey Astafiev

    (Karelian Research Center of RAS
    Petrozavodsk State University)

  • Alexander Golovin

    (Karelian Research Center of RAS
    Petrozavodsk State University)

Abstract

In this paper we study a simultaneous service multiserver system which we call speed-scaling supercomputer, where speed-scaling is used to address the performance/power demand tradeoff. We treat the system by three-level modeling approach, using matrix-analytic method, generalized semi-Markov processes and small-scale technical system as the three levels of modeling. An explicit form of stability condition is obtained for a two-server system with heterogeneous customer classes. Regenerative estimation approach is used for confidence estimation of performance measures both in simulation and technical models. We demonstrate the potential of the three-level modeling approach on a relatively sophisticated and interesting model by performing extensive experiments.

Suggested Citation

  • Alexander Rumyantsev & Robert Basmadjian & Sergey Astafiev & Alexander Golovin, 2023. "Three-level modeling of a speed-scaling supercomputer," Annals of Operations Research, Springer, vol. 331(2), pages 649-677, December.
  • Handle: RePEc:spr:annopr:v:331:y:2023:i:2:d:10.1007_s10479-022-04830-0
    DOI: 10.1007/s10479-022-04830-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04830-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-022-04830-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:331:y:2023:i:2:d:10.1007_s10479-022-04830-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.