Relative competitive analysis of cache replacement policies

Abstract

Caches are commonly employed to hide the latency gap between memory and the CPU by exploiting locality in memory accesses. On today's architectures a cache miss may cost several hundred CPU cycles. In order to fulfill stringent performance requirements, caches are now also used in hard real-time systems. In such systems, upper and sometimes also lower bounds on the execution times of a task have to be computed. To obtain tight bounds, timing analyses must take into account the cache architecture. However, developing cache analyses -- analyses that determine whether a memory access is a hit or a miss -- is a difficult problem for some cache architectures. In this paper, we present a tool to automatically compute relative competitive ratios for a large class of replacement policies, including LRU, FIFO, and PLRU. Relative competitive ratios bound the performance of one policy relative to the performance of another policy. These performance relations allow us to use cache-performance predictions for one policy to compute predictions for another, including policies that could previously not be dealt with.