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J. C. Browne

Research and Advances Oct 1 1978

Models for parallel processing within programs: application to CPU: I/O and I/O: I/O overlap

Approximate queueing models for internal parallel processing by individual programs in a multiprogrammed system are developed in this paper. The solution technique is developed by network decomposition. The models are formulated in terms of CPU:I/O and I/O:I/O overlap and applied to the analysis of these problems. The percentage performance improvement from CPU:I/O overlap is found to be greatest for systems which are in approximate CPU:I/O utilization balance and for low degrees of multiprogramming. The percentage improvement from I/O:I/O overlap is found to be greatest for systems in which the I/O system is more utilized than the CPU.
Artificial Intelligence and Machine Learning

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Author Archives

Research and Advances Aug 1 1978

Feedback coupled resource allocation policies in the multiprogramming-multiprocessor computer system

Model studies of some integrated, feedback-driven scheduling systems for multiprogrammed-multiprocessor computer systems are presented. The basic control variables used are the data-flow rates for the processes executing on the CPU. The model systems feature simulated continuous-flow and preempt-resume scheduling of input-output activity. Attention is given to the amount of memory resource required for effective processing of the I/O activity (buffer space assignment). The model studies used both distribution-driven and trace-driven techniques. Even relatively simple dynamic schedulers are shown to improve system performance (as measured by user CPU time) over that given by optimal or near-optimal static schedulers imbedded in identical system structures and workload environments. The improvement is greatest under a heavy I/O demand workload.
Computing Applications
Research and Advances Mar 1 1977

Memory management and response time

This paper presents a computationally tractable methodology for including accurately the effects of finite memory size and workload memory requirements in queueing network models of computer systems. Empirical analyses and analytic studies based on applying this methodology to an actual multiaccess interactive system are reported. Relations between workload variables such as memory requirement distribution and job swap time, and performance measures such as response time and memory utilization are graphically displayed. A multiphase, analytically soluble model is proposed as being broadly applicable to the analysis of interactive computer systems which use nonpaged memories.
Research and Advances Dec 1 1972

Trace-driven modeling and analysis of CPU scheduling in a multiprogramming system

Microscopic level job stream data obtained in a production environment by an event-driven software probe is used to drive a model of a multiprogramming computer system. The CPU scheduling algorithm of the model is systematically varied. This technique, called trace-driven modeling, provides an accurate replica of a production environment for the testing of variations in the system. At the same time alterations in scheduling methods can be easily carried out in a controlled way with cause and effects relationships being isolated. The scheduling methods tested included the best possible and worst possible methods, the traditional methods of multiprogramming theory, round-robin, first-come-first-served, etc., and dynamic predictors. The relative and absolute performances of these scheduling methods are given. It is concluded that a successful CPU scheduling method must be preemptive and must prevent a given job from holding the CPU for too long a period.

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