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StatCache: a probabilistic approach to efficient and accurate data locality analysis

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2 Author(s)
Berg, E. ; Dept. of Inf. Technol., Uppsala Univ., Sweden ; Hagersten, E.

The widening memory gap reduces performance of applications with poor data locality. Therefore, there is a need for methods to analyze data locality and help application optimization. In this paper we present StatCache, a novel sampling-based method for performing data-locality analysis on realistic workloads. StatCache is based on a probabilistic model of the cache, rather than a functional cache simulator. It uses statistics from a single run to accurately estimate miss ratios of fully-associative caches of arbitrary sizes and generate working-set graphs. We evaluate StatCache using the SPEC CPU2000 benchmarks and show that StatCache gives accurate results with a sampling rate as low as 10-4. We also provide a proof-of-concept implementation, and discuss potentially very fast implementation alternatives.

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Performance Analysis of Systems and Software, 2004 IEEE International Symposium on - ISPASS

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