Probability Models for Multiprogramming Computer Systems

ABSTRACT

A probabilistic model is developed for a multiprogramming computer configuration, i.e., one in which several program segments are simultaneously in main memory (core). The model relates speed and number of input-output devices, core size, and central processor speed to central processor and system productivity. Incorporated in the model are parameters describing the statistical variability of input-output and central processor activities. Thus the model permits comparisons between systems loaded with different mixtures of job types (“scientific” vs. “business” applications). Numerical comparisons of various systems are provided.

REFERENCES

• 1: Wei Chang , Donald J. Wong, Analysis of Real Time Multiprogramming, Journal of the ACM (JACM), v.12 n.4, p.581-588, Oct. 1965 [doi>10.1145/321296.321309]
• 2: Jack B. Dennis, Segmentation and the Design of Multiprogrammed Computer Systems, Journal of the ACM (JACM), v.12 n.4, p.589-602, Oct. 1965 [doi>10.1145/321296.321310]
• 3: FELLER, W. An Introduction to Probability Theory, Vols. I, II. Wiley, New York, 1950.
• 4: GAVER, D.P. A waiting line with interrupted service, including priorities. J. Roy. Statist. Soc. {B}, 24, 1 (1962), 73-90.
• 5: HAMERSLEY, J. M., AND HNDSCOMB, D. C. Monte Carlo Methods. Methuen Monograph, Wiley, New York, 1964.
• 6: MoRsE, PHILIP M. Queues, Inventories, and Maintenance. Wiley, New York, 1958.

INDEX TERMS

Primary Classification:
  D. Software
  D.4 OPERATING SYSTEMS
      D.4.1 Process Management
          Subjects: Multiprocessing/multiprogramming/multitasking

Additional Classification:
  F. Theory of Computation
  F.1 COMPUTATION BY ABSTRACT DEVICES
      F.1.2 Modes of Computation
          Subjects: Probabilistic computation

General Terms:
Measurement, Performance, Theory