Hotspot-Aware Hybrid Memory Management for In-Memory Key-Value Stores

Abstract

Emerging Non-Volatile Memory (NVM) technologies promise much higher memory density and energy efficiency than DRAM, at the expense of higher read/write latency and limited write endurance. Hybrid memory systems composed of DRAM and NVM have the potential to provide very large capacity of main memory for in-memory key-value (K-V) stores. However, there remains challenges to directly deploy DRAM-based K-V stores in hybrid memory systems. The performance and energy efficiency of K-V stores on hybrid memory systems have not been fully explored yet. In this paper, we propose HMCached, an in-memory K-V store built on a hybrid DRAM/NVM system. HMCached utilizes an application-level data access counting mechanism to identify frequently-accessed (hotspot) objects (i.e., K-V pairs) in NVM, and migrates them to fast DRAM to reduce the costly NVM accesses. We also propose an NVM-friendly index structure to store the frequently-updated portion of object metadata in DRAM, and thus further mitigate the NVM accesses. Moreover, we propose a benefit-aware memory reassignment policy to address the slab calcification problem in slab-based K-V store systems, and significantly improve the benefit gain from the DRAM. We implement the proposed schemes with Memcached and evaluate it with Zipfian-like workloads. Experiment results show that HMCached significantly reduces NVM accesses by 70 percent compared to the vanilla Memcached running on a DRAM/NVM hybrid memory system without any optimizations, and improves application performance by up to 50 percent. Moreover, compared to a DRAM-only system, HMCached achieves 90 percent of performance and 46 percent reduction of energy consumption for realistic (read-intensive) workloads while significantly reducing the DRAM usage by 75 percent.

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