UART Publications
StatCache: A Probabilistic Approach to Efficient and Accurate Data Locality Analysis
Erik Berg and Erik Hagersten
In Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS-2004), Austin, Texas, USA, March 2004.
Abstract
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 Stat-Cache, 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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BibTeX file entry: Berg:2004:mar