This work proposes several new schemes for the replacement of cache lines/blocks in high performance computer systems. Our algorithms rely on judiciously chosen neural networks for accurate real-time statistical predictions. These algorithms, therefore, provide better cache performance as compared to the conventional LRU (Least Recently Used) algorithm. Simulation results indicate that the proposed set of replacement strategies can provide a performance improvement of as much as 16.4711% over the LRU algorithm for our selected benchmark trace files. The results are based on an experimentation involving 6 neural network paradigms and 21 different cache configurations. Excellent performance of the neural network-based replacement strategies means that this new approach can be studied as an alternative to the existing page replacement and prefetching algorithms in virtual memory systems.
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The unconventional replacement algorithms
Khalid, Humayun
Follow ACM SIGARCH Computer Architecture News
, Volume 23 (5)
Association for Computing Machinery – Dec 15, 1995
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