Efficient shared cache management through sharing-aware replacement and streaming-aware insertion policy

Multi-core processors with shared caches are now commonplace. However, prior works on shared cache management primarily focused on multi-programmed workloads. These schemes consider how to partition the cache space given that simultaneously-running applications may have different cache behaviors. In this paper, we examine policies for managing shared caches for running single multi-threaded applications. First, we show that the shared-cache miss rate can be significantly reduced by reserving a certain amount of space for shared data. Therefore, we modify the replacement policy to dynamically partition each set between shared and private data. Second, we modify the insertion policy to prevent streaming data (data not reused before eviction) from promoting to the MRU position. Finally, we use a low-overhead sampling mechanism to dynamically select the optimal policy. Compared to LRU policy, our scheme reduces the miss rate on average by 8.7% on 8 MB caches and 20.1% on 16 MB caches respectively.