Predicting Data Cache Misses in Non-Numeric Applications Through Correlation Profiling

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Predicting Data Cache Misses in Non-Numeric Applications Through Correlation Profiling (1997)

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by Todd Mowry , Chi-keung Luk

Venue:	In MICRO-30
Citations:	38 - 4 self

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@INPROCEEDINGS{Mowry97predictingdata,
    author = {Todd Mowry and Chi-keung Luk},
    title = {Predicting Data Cache Misses in Non-Numeric Applications Through Correlation Profiling},
    booktitle = {In MICRO-30},
    year = {1997},
    pages = {314--320}
}

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Abstract

To maximize the benefit and minimize the overhead of software-based latency tolerance techniques, we would like to apply them precisely to the set of dynamic references that suffer cache misses. Unfortunately, the information provided by the state-of-theart cache miss profiling technique (summary profiling) is inadequate for references with intermediate miss ratios---it results in either failing to hide latency, or else inserting unnecessary overhead. To overcome this problem, we propose and evaluate a new technique--- correlation profiling---which improves predictability by correlating the caching behavior with the associated dynamic context. Our experimental results demonstrate that roughly half of the 22 non-numeric applications we study can potentially enjoy significant reductions in memory stall time by exploiting at least one of the three forms of correlation profiling we consider. 1 Introduction As the disparity between processor and memory speeds continues to grow, memory l...

Keyphrases

correlation profiling non-numeric application data cache miss new technique correlation associated dynamic context significant reduction experimental result dynamic reference summary profiling cache miss unnecessary overhead memory stall time memory speed intermediate miss ratio state-of-theart cache miss profiling technique software-based latency tolerance technique

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