Predicting Performance Degradation on Adaptive Cache Replacement Policy

Adaptive Cache Replacement Policy (ACRP) has been implemented in recently proposed commercial multi-core processors. ACRP consists of two candidate cache replacement policies and dynamically employs the policy which is with fewer cache misses at the moment. ACRP can diminish the overall cache misses, but at the same time it augments the performance inference between co-running applications and makes the performance prediction much harder. Unfortunately, very little work has focused on the performance impact from this mechanism. In this paper, we firstly expose the performance variation problem due to adaptive cache replacement policies. Secondly, we present Bubble-Bound, a low-overhead measurement-based method to estimate a program's performance variation caused by the dynamic adaptation of cache replacement policies. By using a stress program to characterize the pressure and sensitivity, our method can predict a bound for the performance degradation between co-located applications and enable “safe” co-locations on the processors with ACRP.