Memshare: a Dynamic Multi-tenant Key-value Cache

Authors: 

Asaf Cidon, Stanford University; Daniel Rushton, University of Utah; Stephen M. Rumble, Google Inc.; Ryan Stutsman, University of Utah

Abstract: 

Web application performance heavily relies on the hit rate of DRAM key-value caches. Current DRAM caches statically partition memory across applications that share the cache. This results in under utilization and limits cache hit rates. We present Memshare, a DRAM key-value cache that dynamically manages memory across applications. Memshare provides a resource sharing model that guarantees reserved memory to different applications while dynamically pooling and sharing the remaining memory to optimize overall hit rate.

Key-value caches are typically memory capacity bound, which leaves cache server CPU and memory bandwidth idle. Memshare leverages these resources with a log-structured design that allows it to provide better hit rates than conventional caches by dynamically re-partitioning memory among applications. We implemented Memshare and ran it on a week-long trace from a commercial memcached provider. Memshare increases the combined hit rate of the applications in the trace from 84.7% to 90.8%, and it reduces the total number of misses by 39.7% without significantly affecting cache throughput or latency. Even for single-tenant applications, Memshare increases the average hit rate of the state-of-the-art key-value cache by an additional 2.7%.

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BibTeX
@inproceedings {203165,
author = {Asaf Cidon and Daniel Rushton and Stephen M. Rumble and Ryan Stutsman},
title = {Memshare: a Dynamic Multi-tenant Key-value Cache},
booktitle = {2017 {USENIX} Annual Technical Conference ({USENIX} {ATC} 17)},
year = {2017},
isbn = {978-1-931971-38-6},
address = {Santa Clara, CA},
pages = {321--334},
url = {https://www.usenix.org/conference/atc17/technical-sessions/presentation/cidon},
publisher = {{USENIX} Association},
}