Analyzing multiprocessor cache behavior through data reference modeling

Abstract

This paper develops a data reference modeling technique to estimate with high accuracy the cache miss ratio in cache-coherent multiproeessors. The technique involves analyzing the dynamic data referencing behavior of parallel algorithms. Data referenee modeling first identifies different types of shared data blocks accessed during the execution of a parallel algorithm, then captures in a few parameters the cache behavior of each shared block as a function of the problem size, number of processors, and cache line size, and finally constructs an analytical expression for each algorithm to estimate the cache miss ratio. Because the number of processors, problem size, and cache line size are included as parameters, the expression for the each miss ratio can be used to predict the performance of systems with different configurations. Six parallel algorithms are studied, and the analytical results compared against previously published simulation results, to establish the confidence level of the data reference modeling technique. It is found that the average prediction error for four out of six algorithms is within five percent and within ten percent for the other two. The paper also derives from the model several results on how cache miss rates scale with system size.