Predicting whole-program locality through reuse distance analysis
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Miss Rate Prediction across All Program Inputs
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Concurrency and Computation: Practice & Experience - Parallel and Distributed Computing (EuroPar 2005)
IEEE Transactions on Software Engineering
Characterizing the Relation Between Apex-Map Synthetic Probes and Reuse Distance Distributions
ICPP '10 Proceedings of the 2010 39th International Conference on Parallel Processing
All-window profiling and composable models of cache sharing
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming
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A footprint is the volume of data accessed in a time window. A complete characterization requires summarizing all footprints in all execution windows. A concise summary is the footprint curve, which gives the average footprint in windows of different lengths. The footprint curve contains information from all footprints. It can be measured in time O(n) for a trace of length n, which is fast enough for most benchmarks. In this paper, we outline a study on footprint curves. We propose four curve fitting methods based on the real data observed in SPEC benchmark programs.