Abstract
This paper describes a methodology for a very efficient characterization of a workload’s memory access properties using the least recently used (LRU) replacement policy. The resulting access reuse profile captures working set sizes of a workload and can be used to characterize the amount of locality of data references and predict its general caching behavior.
The approach discussed in this paper is flexible and can be used in conjunction with tracing or execution-driven techniques. Because of the efficiency of the proposed algorithm – processing over one million memory accesses per second – the LRU profiles can be collected for a large number of workloads and the resulting data can be used in early stages of computer system design.
We illustrate the method with data collected for NAS Parallel Benchmarks. For selected benchmarks we compare the miss rate profiles for various sizes of the workload. We also compare the resulting LRU profiles with point predictions of miss rates generated with conventional cache simulations and observe a good match. In the concluding part of the paper we report the performance results for the proposed method.
This material is based upon work supported by DARPA under Contract No. NBCH3039002 and by the Australian Research Council Linkage Grant LP0347178.
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Bonebakker, L., Over, A., Sharapov, I. (2006). Working Set Characterization of Applications with an Efficient LRU Algorithm. In: Horváth, A., Telek, M. (eds) Formal Methods and Stochastic Models for Performance Evaluation. EPEW 2006. Lecture Notes in Computer Science, vol 4054. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11777830_6
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DOI: https://doi.org/10.1007/11777830_6
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