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by frankmcsherry
3109 days ago
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In case anyone wants to check out some pre-history, back in 2002 Manfred Warmuth et al.[0] were using learning (Weighted Majority) to drive systems components like cache replacement policy. I'm not sure where the work went from there, but add it to the pile of techniques. [0]: https://users.soe.ucsc.edu/~sbrandt/papers/NIPS02.pdf |
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Reading your cite, the practical issue seems to me to be that the optimizer's memory footprint costs may in fact negate any benefit (e.g. ~40% over LRU) obtained in reducing cache misses.
My gut feeling is that this approach (for online systems) may work best with a hardware component (a card hosting the 'experts' and their virtual model e.g. the "virtual cache"). The distributed variant also seems worth exploring.
[1]: https://arxiv.org/pdf/1403.0388.pdf