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Reuse-based Analytical Models for Caches

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Author(s)
Wood, David A.; Sen, Rathijit
Citation
TR1706
Date
Nov 18, 2011
Subject(s)
RANDOM; PLRU; LRU; repalcement policies; reuse distance; stack distance; cache
Abstract
We develop a reuse distance/stack distance based analytical modeling framework for efficient, online prediction of cache performance for a range of cache configurations and replacement policies LRU, PLRU, RANDOM, NMRU. Such a predictive framework can be extremely useful in selecting the optimal parameters in a dynamic reconfiguration environment that performs power-shifting or resource reallocation through cache partitioning. Our framework unifies existing cache miss-rate prediction techniques such as Smith?s associativity model, Poisson variants, and hardware way-counter based schemes. We also show how to adapt way-counters to work when the number of sets in the cache changes. We propose a novel low-overhead hardware mechanism to estimate reuse distance/stack distance distributions using a combination of set-sampling and time-sampling. This can be used even in cases where using way-counters is not possible, e.g. RANDOM/NMRU replacement policies.
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http://digital.library.wisc.edu/1793/60995 
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