J. D. Noe
Abstract
Is the load on your computer shifting? Did that change to faster access disks really help? Would more core memory increase throughput appreciably, or would it be necessary to also increase central processor power? These are three quite different kinds of questions; one concerns detecting a long-term trend, another assessing the effects of a system change, and a third estimating effects of the decision to alter the configuration. Yet all of these require knowledge of current and past system performance, the type of knowledge that must be the result of long-term performance monitoring. This is not simple enough to be picked up overnight or in one series of experiments, nor can it be assessed by watching one or two parameters over a long period. One must have a thorough understanding of the pattern of performance by knowing the mean values of a number of measures and knowing something about the variations from these means.
This paper hardly needs to recommend that computer managers establish an understanding of performance pattern; they already are very conscious of the need. What it does is recount development of a method of doing so for the CDC 6400 at the University of Washington and of the selection of “Kiviat Graphs” as a means to present data in a synoptic form.
The remainder of this paper will give a brief account of the authors' experience in designing a measurement system for the CDC 6400 at the University of Washington Computer Center. This will include comments on the approach to deciding what to measure an d display for the synoptic view of the system, as well as how to provide more detailed data for backup. Examples of the use of Kiviat Graphs [4] to show the effects of load shift and of a system configuration change are included, and the effect of a change of operating system will be noted.
- 1 Yeh, J. and Minker, J. "KWIC Index and Bibliography on Computer Systems Evaluation Techniques", University of Maryland, TR-246 NGR 21-002-197, June 1973.Google Scholar
- 2 ACM Performance Evaluation Review, V. 2, No. 2, June 1973, pp. 37-49Google Scholar
- 3 Bell, T. E., Boehm, B. W., Watson, R. A., "Framework and Initial Phases for Computer Performance Improvement", Fall Joint Computer Conf., 1972, pp. 1141-1154.Google Scholar
- 4 Kiviat, P. J., Kolence, K. W., "Software Unit Profiles and Kiviat Figures", V. 2, No. 3, September 1973. Google ScholarDigital Library
- 5 Ferrari, D., "Workload Characterization and Selection in Computer Performance Measurement", Computer, July/August, 1972, pp. 18-24.Google Scholar
- 6 Buchholz, W., "A Synthetic Job for Measuring Systems Performance" IBM Systems Journal, V. 8, No. 4, 1969, pp. 309-318.Google Scholar
- 7 Snyder, R., "A Quantitative Study of the Addition of Extended Core Storage", ACM Performance Evaluation Review, V. 3, No. 1, March 1974, pp. 10-33. Google ScholarDigital Library
Index Terms
- Develop your computer performance pattern
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Develop your computer performance pattern
SIGMETRICS '74: Proceedings of the 1974 ACM SIGMETRICS conference on Measurement and evaluationIs the load on your computer shifting? Did that change to faster access disks really help? Would more core memory increase throughput appreciably, or would it be necessary to also increase central processor power? These are three quite different kinds ...
Comments on the computer science/computer center interface
SIGUCCS '72: Proceedings of the annual ACM SIGUCCS symposium on The administration and management of small-college computing centersI'd like to find out how many people in this group come from institutions of 4000 or more students. How many of you come from institutions of 2500 or less? How many come from institutions of 1000 or less students? How many of you have your own computer? ...
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