Guiding the Optimization of Parallel Codes on Multicores Using an Analytical Cache Model

Abstract

Cache performance is particularly hard to predict in modern multicore processors as several threads can be concurrently in execution, and private cache levels are combined with shared ones. This paper presents an analytical model able to evaluate the cache performance of the whole cache hierarchy for parallel applications in less than one second taking as input their source code and the cache configuration. While the model does not tackle some advanced hardware features, it can help optimizers to make reasonably good decisions in a very short time. This is supported by an evaluation based on two modern architectures and three different case studies, in which the model predictions differ on average just 5.05% from the results of a detailed hardware simulator and correctly guide different optimization decisions.