HASDH: A Hotspot-Aware and Scalable Dynamic Hashing for Hybrid DRAM-NVM Memory

Abstract

Intel Optane DC Persistent Memory Module (DCPMM) is the first commercially available non-volatile memory (NVM) product and can be directly placed on the processor’s memory bus along with DRAM to serve as a hybrid memory. Compared with DRAM, NVM has 3× read latency and similar write latency, while the read and write bandwidths of NVM are only 1/3rd and 1/6th of those of DRAM. However, existing hashing schemes fail to reap those performance characteristics. We propose HASDH, a hotspot-aware and scalable dynamic hashing built on the hybrid DRAM-NVM memory. HASDH maintains structure metadata (i.e., directory) in DRAM and persists key-value items in NVM. To reduce hot key-value items’ access cost, HASDH caches frequently-accessed key-value items in DRAM with a dedicated caching strategy. To achieve scalable performance for multicore machines, HASDH maintains locks in DRAM that avoid the extra NVM read-write bandwidth consumption caused by lock operations. Furthermore, HASDH chains all NVM segments using sibling pointers to the right neighbors to ensure crash consistency and leverages log-free NVM segment split to reduce logging overhead. On an 18-core machine with Intel Optane DCPMM, experimental results show that HASDH achieves 1.43∼7.39× speedup for insertions, 2.08~9.63× speedup for searches, and 1.78~3.01× speedup for deletions, compared with start-of-the-art NVM-based hashing indexes.