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Comparison of analytic performance models using closed mean-value analysis versus open-queuing theory for estimating cycles per instruction of memory hierarchies

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1 Author(s)
R. E. Matick ; IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA

Analytic models provide a simple but approximate method for predicting the performance of complex processing systems early in the design cycle. Over the years, extensive use has been made of various queuing models to analyze the memory hierarchies of multiprocessor systems in order to estimate the finite cache penalty and resulting system performance measured in cycles per instruction executed. Two general modeling techniques widely used for such performance evaluation are the open-system and closed-system queuing theories. Closed-queuing models can be solved by various methods, but mean value analysis is the most common for closed systems of the type considered here. The basic differences between these two approaches have been somewhat obscure, making them difficult to compare. This work explores some fundamental issues from a practical engineering viewpoint with the intention of illuminating the essential differences in the general techniques at the very basic level. In addition, the results of a detailed study comparing the two in a moderately complex multiprocessor memory hierarchy are presented.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:47 ,  Issue: 4 )