A Mean Value Analysis Multiprocessor Model Incorporating Superscalar Processors and Latency Tolerating Techniques

Abstract

Several approximate Mean Value Analysis (MVA) shared memory multiprocessor models have been developed and used to evaluate a number of system architectures. In recent years, the use of superscalar processors, multilevel cache hierarchies, and latency tolerating techniques has significantly increased the complexity of multiprocessor system modeling. We present an analytical performance model which extends previous multiprocessor MVA models by incorporating these new features and in addition, increases the level of modeling detail to improve flexibility and accuracy. The extensions required to analyze the impact of these new features are described in detail. We then use the model to demonstrate some of the tradeoffs involved in designing modern multiprocessors, including the impact of highly superscalar architectures on the scalability of multiprocessor systems.