Lecture Notes in Computer Science, 2001, Volume 2153/2001, 61-77, DOI: 10.1007/3-540-44808-X_5

Experimental Results on Statistical Approaches to Page Replacement Policies

Vitus Leung and Sandy Irani

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Abstract

This paper investigates the questions of what statistical information about a memory request sequence is useful to have in making page replacement decisions. Our starting point is the Markov Request Model for page request sequences. Although the utility of modeling page request sequences by the Markov model has been recently put into doubt ([13]), we find that two previously suggested algorithms (Maximum Hitting Time [11] and Dominating Distribution [14]) which are based on the Markov model work well on the trace data used in this study. Interestingly, both of these algorithms perform equally well despite the fact that the theoretical results for these two algorithms differ dramatically. We then develop succinct characteristics of memory access patterns in an attempt to approximate the simpler of the two algorithms. Finally, we investigate how to collect these characteristics in an online manner in order to have a purely online algorithm.
Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under contract DE-AC04-94AL 85000. Part of this work was done while at the University of California, Irvine and supported by NSF Grant CCR-9309456.
Supported in part by NSF Grant CCR-9309456.

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