Memshare: a Dynamic Multi-tenant Memory Key-value Cache
  Web application performance is heavily reliant on the hit rate of memory-based caches. Current DRAM-based web caches statically partition their memory across multiple applications sharing the cache. This causes under utilization of memory which negatively impacts cache hit rates. We present Memshare, a novel web memory cache that dynamically manages memory across applications. Memshare provides a resource sharing model that guarantees private memory to different applications while dynamically allocating the remaining shared memory to optimize overall hit rate. Today's high cost of DRAM storage and the availability of high performance CPU and memory bandwidth, make web caches memory capacity bound. Memshare's log-structured design allows it to provide significantly higher hit rates and dynamically partition memory among applications at the expense of increased CPU and memory bandwidth consumption. In addition, Memshare allows applications to use their own eviction policy for their objects, independent of other applications. We implemented Memshare and ran it on a week-long trace from a commercial memcached provider. We demonstrate that Memshare increases the combined hit rate of the applications in the trace by an 6.1% (from 84.7% hit rate to 90.8% hit rate) and reduces the total number of misses by 39.7% without affecting system throughput or latency. Even for single-tenant applications, Memshare increases the average hit rate of the current state-of-the-art memory cache by an additional 2.7% on our real-world trace. 
Asaf Cidon, Daniel Rushton, Stephen M. Rumble and Ryan Stutsman
cs.OS