Abstract
A performance analysis methodology using certain aspects of queueing theory to evaluate computer system speed performance is presented. This methodology specifically focuses on modeling multiprocessor computer systems with unbalanced flows (i.e., number of transactions leaving a server is not the same as number of transactions entering that server) due to asynchronously spawned parallel tasks. This unbalanced flow phenomenon, which has a significant effect on performance, cannot be solved analytically by classical queueing network models. A decomposition method is applied to decompose the unbalanced flows. Formulae for open queueing networks with unbalanced flows due to asynchronously spawned tasks are developed. Furthermore, an algorithm based on Buzen's convolution algorithm is developed to test the necessary and sufficient condition for closed system stability as well as to compute performance measures. An average of less than four iterations is reported for convergence with this algorithm. A Study of the INFOPLEX multiprocessor data storage hierarchy, comparing this rapid solution algorithm with simulations, has shown highly consistent results. A cost effective software tool, using this methodology, has been developed to analyze an architectural design, such as INFOPLEX, and to produce measures such as throughput, utilization, and response time so that potential performance problems can be identified.
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