  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.
