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Program behavior prediction and prepaging

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Summary

The design and evaluation of a prepaging technique is presented. It consists in the preloading, at instants at which page-faults occur, of those pages whose use in the future is the most likely. These pages are determined as a function of an a-priori knowledge of program behavior. We shall first present two tools for predicting that behavior. The first is based on a Markov memory reference transition model, the second on a semi-Markov model of page-fault transitions. Both methods are successively experimented by a paging algorithm allowing prepaging. Experimentation shows that prepaging can significantly improve the performance of the paging algorithm, especially when the prediction is based on the transitions between page-faults. The sensitivity of prepaging performance to various working conditions is tested. Implementation of prepaging is examined and is shown to be feasible without the use of special hardware devices. The study is completed by an evaluation of the influence of prepaging on global system performance. Some common cases of system architecture experimentation show a non-negligible increase in CPU utilization.

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  1. IUT 2, 17 Rue de France, F-69100, Villeurbanne, France

    Michel Martinez

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  1. Michel Martinez
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Martinez, M. Program behavior prediction and prepaging. Acta Informatica 17, 101–120 (1982). https://doi.org/10.1007/BF00262979

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