CacheSack: Admission Optimization for Google Datacenter Flash Caches

Authors: 

Tzu-Wei Yang, Seth Pollen, Mustafa Uysal, Arif Merchant, and Homer Wolfmeister, Google

Abstract: 

This paper describes the algorithm, implementation, and deployment experience of CacheSack, the admission algorithm for Google datacenter flash caches. CacheSack minimizes the dominant costs of Google’s datacenter flash caches: disk IO and flash footprint. CacheSack partitions cache traffic into disjoint categories, analyzes the observed cache benefit of each subset, and formulates a knapsack problem to assign the optimal admission policy to each subset. Prior to this work, Google datacenter flash cache admission policies were optimized manually, with most caches using the Lazy Adaptive Replacement Cache (LARC) algorithm. Production experiments showed that CacheSack significantly outperforms the prior static admission policies for a 6.5% improvement of the total operational cost, as well as significant improvements in disk reads and flash wearout.

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BibTeX
@inproceedings {280692,
author = {Tzu-Wei Yang and Seth Pollen and Mustafa Uysal and Arif Merchant and Homer Wolfmeister},
title = {{CacheSack}: Admission Optimization for Google Datacenter Flash Caches},
booktitle = {2022 USENIX Annual Technical Conference (USENIX ATC 22)},
year = {2022},
isbn = {978-1-939133-29-15},
address = {Carlsbad, CA},
pages = {1021--1036},
url = {https://www.usenix.org/conference/atc22/presentation/yang-tzu-wei},
publisher = {USENIX Association},
month = jul,
}

Presentation Video