analysis of critical architectural and programming parameters in a hierarchical
Scalable shared-memory multiprocessors are the subject of much current research, but little is known about the performance behavior of these machines. This paper studies the performance effects of two machine characteristics and two program characteristics that seem to be major factors in determining the performance of a hierarchical shared-memory machine. We develop an analytical model of the traffic in a machine loosely based on Stanford's DASH multiprocessor and use program parameters extracted from multiprocessor traces to study its performance. It is shown that both locality in the data reference stream and the amount of data sharing in a program have an important impact on performance. Although less obvious, the bandwidth within each cluster in the hierarchy also has a significant performance effect. Optimizations that improve the intracluster cache coherence protocol or increase the bandwidth within a cluster can be quite effective.
analysis critic architecture program hierarchic multiprocessor research performance behavior paper effect factor analytic models traffic use traces locality data streams data sharing bandwidth cluster hierarchies optimality cache coherence shared memory shared memory multiprocessors