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Optimal multiprogramming: Principles and implementation

  • Marc Badel
  • Jacques Leroudier
Implementation And Simulation Techniques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 65)

Abstract

Three principles of optimality for multiprogramming are derived from a general model of a virtual memory computer system. They state the existence of both an optimal multiprogramming degree and an optimal program mixture in the multiprogramming set. The implementation of these principles is carefully studied in a simulation model which permits, in contrast to analytical models, to relax assumptions on the workload submitted to the system. More precisely the workload is supposed to be non-stationary and issued from a non-homogeneous program population. Therefore a dynamic control of the system needs special estimators. These statistical problems are studied in detail and an implementation is described. The results obtained on the system performance improvement are presented.

Keywords

Schedule Algorithm Secondary Memory System Performance Improvement Page Fault File Disk 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. [1]
    BADEL M., GELENBE E., LENFANT J., LEROUDTER J., POTIER D. — "Adaptive optimization of the performance of a virtual memory computer" — Proceed. of the Workshop on Computer Architecture and Networks — IRIA — North-Holland Publishing Co. — August 1974.Google Scholar
  2. [2]
    BADEL M., GELENBE E., LEROUDIER J., POTIER D. — "Adaptive optimization of a time-sharing system's performance" — IEEE Proceed. on Interactive Computer Systems — June 1975.Google Scholar
  3. [3]
    LEROUDIER J., POTIER D. — "Principles of optimality for multiprogramming" — ACM-SIGMETRICS and IFIP W.G. 7.3. Conference Harvard University — March 1976.Google Scholar
  4. [4]
    DENNING P.J., KAHN K.C., LEROUDIER J., POTIER D., SURI R. — "Optimal multiprogramming" — Acta Informatica — Vol.7 — Fasc.2 — Dec. 1976.Google Scholar
  5. [5]
    COURTOIS P. — "On the near-complete decomposability of networks of queues and stochastic models of multiprogramming computing systems" MBLE Report — Brussels — Belgium — November 1971.Google Scholar
  6. [6]
    COURTOIS P.J. — "Decomposability, instabilities and saturation in multiprogramming systems" — Communications of ACM — Vol.18 — no7 — July 1975.Google Scholar
  7. [7]
    JACKSON J.R. — "Jobshop-like queueing systems" — Management Science, 10, 1, October 1963.Google Scholar
  8. [8]
    BUZEN J.P. — "Computational algorithms for closed queueing networks with exponential servers" — Communications of ACM — 16, 9, Sept. 1973.Google Scholar
  9. [9]
    CHANG A., LAVENBERG S.S. — "Work-rates in closed queueing networks models" — Operation Research, 22, 1974.Google Scholar
  10. [10]
    POTIER D., LEROUDIER J., BADEL M. — "Un modèle d'analyse des performances d'ordinateurs multiprogrammés à mémoire virtuelle" — Rapport IRIA-LABORIA no 152 — January 1976.Google Scholar
  11. [11]
    LEROUDIER J. — "Systèmes adaptatifs à mémoire virtuelle" — Thèse d' Etat — Grenoble University — May 1977.Google Scholar
  12. [12]
    BELADY L.A., KUEHNER C.J. — "Dynamic space-sharing in computer systems" — Communications of ACM — Vol. 12 — no5 — May 1969.Google Scholar
  13. [13]
    BURGEVIN P., LEROUDIER J. — "Characteristics and models of programs behavior" — National Conference ACM 76 — Houston — Texas — Oct. 1976Google Scholar
  14. [14]
    BURGEVIN P., INGELS Ph., LEROUDIER J. — "Analysis of program behaviour" — Rapport IRIA-LABORIA no 237 — June 1977.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1978

Authors and Affiliations

  • Marc Badel
    • 1
  • Jacques Leroudier
    • 1
  1. 1.Iria - LaboriaLe ChesnayFrance

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