Efficient profile-based evaluation of randomising set index functions for cache memories

The performance of direct mapped caches is degraded by conflict misses. It has been shown that conflict misses can be reduced by using randomising set index functions, such that repeated conflicts are avoided. However, optimising the set index function requires time consuming simulations, because the design space of randomising set index functions is very large. Therefore, we dei,eloped a profile-based technique that allows one to make a fast estimation of the miss ratio incurred by a set index function. Using this technique, one can perform a fast, initial exploration of the design space of set index functions, followed by a slower, but more accurate, analysis using simulation. The profile-based technique is based on a new representation of randomising set index functions using mill spaces. The profile-based technique consists of two phases. In the first phase, a program is profiled and in the second phase, a score is computed from the profile data and the mill space of a set index function. We show that the computed score closely reflects the miss ratio incurred by that set index function. Computing a score is a simple operation that requires no simulation time. Therefore, only one profiling run is required to estimate the miss ratios for a wide range of set index functions.