In this paper, we proposed an effective and efficient multi-core shared-cache design optimization approach based on reuse-distance analysis of the data traces of target applications. Since data traces are independent of system hardware architectures,
a designer can easily compute the best cache design at the early system design phase using our approach. We devise a very efficient and yet accurate method to derive the aggregated reuse-distance histograms of concurrent applications for accurate cache performance analysis and optimization. Essentially, the actual shared-cache contention results of concurrent applications are embedded in the aggregated reuse-distance histograms and therefore the approach is very effective. The experimental results show that the average error rate of shared-cache miss-count estimations of our approach is less than 2.4%. Using a simple scanning search method, one can easily determine the true optimal cache configurations at the early system design phase.
