Faster Functional Warming with Cache Merging

Smarts-like sampled hardware simulation techniques achieve good accuracy by simulating many small portions of an application in detail. However, while this reduces the simulation time, it results in extensive cache warming times, as each of the many simulation points requires warming the whole memory hierarchy. Adaptive Cache Warming reduces this time by iteratively increasing warming to achieve sufficient accuracy. Unfortunately, each increases requires that the previous warming be redone, nearly doubling the total warming. We address re-warming by developing a technique to merge the cache states from the previous and additional warming iterations. We demonstrate our merging approach on multi-level LRU cache hierarchy and evaluate and address the introduced errors. Our experiments show that Cache Merging delivers an average speedup of 1.44 ×, 1.84 ×, and 1.87 × for 128kB, 2MB, and 8MB L2 caches, respectively, (vs. a 2 × theoretical maximum speedup) with 95-percentile absolute IPC errors of only 0.029, 0.015, and 0.006, respectively. These results demonstrate that Cache Merging yields significantly higher simulation speed with minimal losses.