Fast Data-Locality Profiling of Native Execution

Abstract

Performance tools based on hardware counters can efficiently profile the cache behavior of an application and help software developers improve its cache utilization. Simulator-based tools can potentially provide more insights and flexibility and model many different cache configurations, but have the drawback of large run-time overhead. We present StatCache, a performance tool based on a statistical cache model. It has a small run-time overhead while providing much of the flexibility of simulator-based tools. A monitor process running in the background collects sparse memory access statistics about the analyzed application running natively on a host computer. Generic locality information is derived and presented in a code-centric and/or data-centric view. We evaluate the accuracy and performance of the tool using ten SPEC CPU2000 benchmarks. We also exemplify how the flexibility of the tool can be used to better understand the characteristics of cache-related performance problems.

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BibTeX file entry: Berg:2005:jun