Data Management

Revisiting Locality of Reference in Scientific Grid Workloads

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Executive Summary

This paper revisits a basic question in data management, namely whether locality of reference is an important factor for the performance of caches in grid workloads. The authors answer this question by experimental evaluations using more than two years of real workloads from a science collaboration. The results show that: Locality of reference is significant for these particular workloads and thus it is beneficial to consider it in cache replacement algorithms; and using locality of reference and data request reordering gives better performance along multiple performance metrics than either one of these techniques.

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