SmartIndex: Learning to Index Caches to Improve Performance

Modern computers rely heavily on caches to achieve higher performance. Unfortunately, a cache indexing scheme can often cause an uneven distribution of addresses across cache sets resulting in many evictions of useful cache blocks. To address this issue, we propose SmartIndex , a self-optimized inde...

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Bibliographic Details
Published inIEEE computer architecture letters Vol. 22; no. 1; pp. 33 - 36
Main Authors Weston, Kevin, Mahmud, Farabi, Janfaza, Vahid, Muzahid, Abdullah
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Associativity
Cache
Computational modeling
conflict miss
Cryptography
Hardware
Hash functions
Indexing
Machine learning
Performance enhancement
Performance indices
Predictive models
Training
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Summary:Modern computers rely heavily on caches to achieve higher performance. Unfortunately, a cache indexing scheme can often cause an uneven distribution of addresses across cache sets resulting in many evictions of useful cache blocks. To address this issue, we propose SmartIndex , a self-optimized indexing scheme that leverages machine learning to actively learn the memory access pattern and dynamically adjust indexes to evenly distribute the cache lines across all sets in the cache, thereby reducing cache misses. Experimental results on a set of 26 memory-intensive applications show that for non-uniform applications, SmartIndex can reduce the misses per kilo instructions (MPKI) of a direct mapped cache by up to 39%, translating into an IPC speedup of 7.23% compared to the conventional power-of-two indexing scheme. Our experiments also show that SmartIndex can work with any cache associativity.
ISSN:1556-6056
1556-6064
DOI:10.1109/LCA.2023.3264478