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

被引:1
作者
Yang, Tzu-Wei [1 ]
Pollen, Seth [2 ]
Uysal, Mustafa [1 ]
Merchant, Arif [1 ]
Wolfmeister, Homer [2 ]
Khalid, Junaid [2 ]
机构
[1] Google, 1600 Amphitheatre Pkwy, Mountain View, CA 94043 USA
[2] Google, 811 E Washington Ave,Suite 700, Madison, WI 53703 USA
关键词
Flash caches; distributed storage systems;
D O I
10.1145/3582014
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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).
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页数:24
相关论文
共 44 条
[1]  
Albrecht Christoph, 2013, Proceedings of USENIX ATC '13: 2013 USENIX Annual Technical Conference. ATC '13, P91
[2]   ANOTHER EFFICIENT ALGORITHM FOR CONVEX HULLS IN 2 DIMENSIONS [J].
ANDREW, AM .
INFORMATION PROCESSING LETTERS, 1979, 9 (05) :216-219
[3]  
[Anonymous], 2003, P 19 ACM S OP SYST P
[4]  
Barr Jeff, 2021, AQUA (Advanced Query Accelerator) - A Speed Boost for Your Amazon Redshift Queries
[5]  
Beckmann N, 2018, PROCEEDINGS OF THE 15TH USENIX SYMPOSIUM ON NETWORKED SYSTEMS DESIGN AND IMPLEMENTATION (NSDI'18), P389
[6]   Maximizing Cache Performance Under Uncertainty [J].
Beckmann, Nathan ;
Sanchez, Daniel .
2017 23RD IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTER ARCHITECTURE (HPCA), 2017, :109-120
[7]   A STUDY OF REPLACEMENT ALGORITHMS FOR A VIRTUAL-STORAGE COMPUTER [J].
BELADY, LA .
IBM SYSTEMS JOURNAL, 1966, 5 (02) :78-&
[8]  
Berg B, 2020, PROCEEDINGS OF THE 14TH USENIX SYMPOSIUM ON OPERATING SYSTEMS DESIGN AND IMPLEMENTATION (OSDI '20), P769
[9]   Towards Lightweight and Robust Machine Learning for CDN Caching [J].
Berger, Daniel S. .
HOTNETS-XVII: PROCEEDINGS OF THE 2018 ACM WORKSHOP ON HOT TOPICS IN NETWORKS, 2018, :134-140
[10]  
Blankstein A, 2017, 2017 USENIX ANNUAL TECHNICAL CONFERENCE (USENIX ATC '17), P499