``Improving Spatial Locality using Data Mining" Karlton Sequeira, Mohammed J. Zaki, Bolek Szymanski, Chris Carothers In Proceedings of the 9th International Conference on Knowledge Discovery and Data Mining, Washington, DC, August 2003.

ABSTRACT


In most computer systems, page fault rate is currently minimized by generic page replacement algorithms, which try to model the temporal locality inherent in programs. In this paper, we propose two algorithms, one greed and the other stochastic, designed for program specific code restructuring as a means of increasing spatial locality within a program. Both algorithms effectively decreas average working set size and hence the page fault rate. Our methods are more effective than traditional approaches due to use of domain information. We illustrate the efficacy of our algorithms on actual data mining algorithms.

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