CacheSack: Theory and Experience of Google’s Admission Optimization for Datacenter Flash Caches

Author:

Yang Tzu-Wei1ORCID,Pollen Seth2ORCID,Uysal Mustafa1ORCID,Merchant Arif1ORCID,Wolfmeister Homer2ORCID,Khalid Junaid2ORCID

Affiliation:

1. Google, Mountain View, CA USA

2. Google, Madison, WI USA

Abstract

This article 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 algorithm. Production experiments showed that CacheSack significantly outperforms the prior static admission policies for a 7.7% improvement of the total cost of ownership, as well as significant improvements in disk reads (9.5% reduction) and flash wearout (17.8% reduction).

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture

Reference44 articles.

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