HDNH: a read-efficient and write-optimized hashing scheme for hybrid DRAM-NVM memory

Abstract

With high memory density, non-volatility and DRAM-scale latency, non-volatile memory (NVM) brings evolution to storage systems and durable data structures. And Intel Optane DC persistent memory module (AEP), the first commercial product of NVM, shows some features that are different from previous assumptions: higher read latency, lower bandwidth and block access granularity compared with DRAM. It is reasonable to build up hybrid memory to give full play to the complementary advantages of DRAM and NVM. In this paper, we present a read-efficient and write-optimized hashing scheme for hybrid DRAM-NVM memory, named HDNH (Hybrid DRAM-NVM Hashing). Our design can be summarized into three key points. First, we decouple the storage for data and metadata by placing key-value items in non-volatile table for persistence while placing metadata in Optimistic Compression Filter (OCF) to reduce excessive NVM accesses. Second, we design hot table in DRAM to speed up search requests and propose an efficient replacement strategy called RAFL. Third, we develop a fine-grained optimistic concurrency mechanism to enable high-performance concurrent accesses on multi-core systems. Experimental results on the AEP platform show that HDNH outperforms its counterparts by up to 2.9x under various YCSB workloads.