Efficient simulation of caches under optimal replacement with applications to miss characterization

Abstract

Cache miss characterization models such as the three Cs model are useful in developing schemes to reduce cache misses and their penalty. In this paper we propose the OPT model that uses cache simulation under optimal (OPT) replacement to obtain a finer and more accurate characterization of misses than the three Cs model. However, current methods for optimal cache simulation are slow and difficult to use. We present three new techniques for optimal cache simulation. First, we propose a limited lookahead strategy with error fixing, which allows one pass simulation of multiple optimal caches. Second, we propose a scheme to group entries in the OPT stack, which allows efficient treebased fully-associative cache simulation under OPT. Third, we propose a scheme for exploiting partial inclusion in set-associative cache simulation under OPT. Simulators based on these algorithms were used to obtain cache miss characterizations using the OPT model for nine SPEC benchmarks. The results indicate that miss ratios under OPT are substantially lower than those under LRU replacement, by up to 70% in fully-associative caches, and up to 32% in t we-way set-associative caches.

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“…The model simplifies the memory timing by differentiating only between sequential and nonsequential read and write accesses. When using other processor architectures, generic cache simulators, such as Dinero IV [25] and Cheetah [26] need to be integrated.…”

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“…Our proposal has some similarity with the way OPT replacement is simulated [13] by an offline trace driven simulator. The simulator typically uses a lookahead window to observe future accesses and pick out the optimal replacement candidate.…”

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