Analytical Modeling of Set-Associative Cache Behavior

Cache behavior is complex and inherently unstable, yet is a critical factor aaecting program performance. A method of evaluating cache performance is required, both to give quantitative predictions of miss-ratio, and information to guide optimization of cache use. Traditional cache simulation gives accurate predictions of miss-ratio, but little to direct optimization. Also, the simulation time is usually far greater than the program execution time. Several analytical models have been developed, but concentrate mainly on direct-mapped caches, often for speciic types of algorithm, or to give qualitative predictions. In this work novel analytical models of cache phenomena are presented, applicable to numerical codes consisting mostly of array operations in looping constructs. Set-associative caches are considered, through an extensive hierarchy of cache reuse and interference eeects, including numerous forms of temporal and spatial locality. Models of each eeect are given, which, when combined, predict the overall miss-ratio. An advantage is that the models also indicate sources of cache interference. The accuracy of the models is validated through example program fragments. The predicted miss-ratios are compared with simulations, and shown typically to be within fteen percent. The evaluation time of the models is shown to be independent of the problem size, generally several orders of magnitude faster than simulation.