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Performance Modeling of Shared-Resource Array Processors

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2 Author(s)
L. M. Ni ; Department of Computer Science, Michigan State University ; Kai Hwang

This paper presents a Markov chain model to analyze the performance of shared-resource array processors for multiple vector processing. Such a parallel processor contains multiple control units sharing a resource pool of processing elements and operating with multiple single-instruction multiple-data streams (MSIMD). In the steady state, the Markov model corresponds to a two-dimensional Markov chain, which can be expressed by a set of equilibrium equations. An iterative method is developed to solve the Markov chain after projecting the equilibrium equations onto a one-dimensional state space. The convergence rate of the iterative method can be greatly enhanced by choosing starting values corresponding to the approximated analytical results obtained earlier by the authors.

Published in:

IEEE Transactions on Software Engineering  (Volume:SE-7 ,  Issue: 4 )