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.
翻译:在本文中,我们提出了一个基于目标应用数据痕量的再利用-远距离分析的有效和高效的多核心共享缓存设计优化方法。由于数据痕量独立于系统硬件结构,设计师可以很容易地使用我们的方法在早期系统设计阶段计算最佳缓存设计。我们设计了一种非常高效和准确的方法,以得出同时应用的合并再利用-远端直径直方图,用于准确缓存性能分析和优化。基本上,同时应用的实际共享缓存争议结果已嵌入到总再利用-远端直方图中,因此该方法非常有效。实验结果显示,我们方法的共享缓存误算估计的平均误差率低于2.4%。使用简单的扫描搜索方法,人们可以很容易确定早期系统设计阶段的真正最佳缓存配置。