Analytical prediction of performance for cache coherence protocols

Abstract

In this paper, we introduce new analytical models for predicting the performance of parallel applications under various cache coherence protocol assumptions. The purpose of these models is to determine which protocols are to be used for which data blocks, and, in the case of dynamic protocols, also to determine when to change protocols. Although we focus on tightly-coupled multiprocessor systems, similar models can be derived for loosely-coupled distributed systems, such as networks of workstations. Our models are unique in that they lie between a large body of theoretical models that assume independence and a uniform distribution of memory accesses across processors, and a large body of address-trace oriented models that assume the availability of a precise characterization of interleaving behavior of memory accesses. The former are not very realistic, and the latter are not suitable for compile-time and run-time usage. In contrast, our models enable us to choose different input parameters depending on how the models will be used and depending on the needed accuracy in performance prediction. We present the models and show how the required parameters can be obtained. We assess the accuracy of our models on 15 parallel applications. For these applications, our most complete model predicts performance within a 10 percent margin when compared to a simulation of a sequentially consistent multiprocessor system. As part of this study, we also show the potential advantage of using dynamic hybrid protocols.