Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Performance analysis of hierarchical cache-consistent multiprocessors
Performance Evaluation - Selected papers from the international seminar on performance of distributed and parallel systems
Understanding some simple processor-performance limits
IBM Journal of Research and Development - Special issue: performance analysis and its impact on design
Analytic evaluation of shared-memory systems with ILP processors
Proceedings of the 25th annual international symposium on Computer architecture
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
IBM Journal of Research and Development
A case study in top-down performance estimation for a large-scale parallel application
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Queuing theoretic model for a multiprocessor with private caches and shared memory
ACM SIGARCH Computer Architecture News
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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.