Fast Modeling L2 Cache Reuse Distance Histograms Using Combined Locality Information from Software Traces
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To mitigate the performance gap between the CPU and the main memory, multi-level cache architectures are widely used in modern processors. Therefore, modeling the behaviors of the downstream caches becomes a critical part of the processor performance evaluation in the early stage of Design Space Exploration (DSE). In this paper, we propose a fast and accurate L2 cache reuse distance histogram model, which can be used to predict the behaviors of the multi-level cache architectures where the L1 cache uses the LRU replacement policy and the L2 cache uses LRU/Random replacement policies. We use the L1 reuse distance histogram and two newly proposed metrics, namely the RST table and the Hit-RDH, that describing more detailed information of the software traces as the inputs. The output of our model is the L2 cache reuse distance histogram, based on which the L2 cache miss rates can be evaluated. We compare the L2 cache miss rates with the results from gem5 cycle-accurate simulations of 15 benchmarks chosen from SPEC2006. The average absolute error is less than 5 model into a multi-core architecture in which two cores share a unified L2 cache. The error of our model, in this case, is less than 7
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