Gengar: An RDMA-based Distributed Hybrid Memory Pool

Byte-addressable Non-volatile Memory (NVM) technologies promise higher density and lower cost than DRAM. They have been increasingly employed for data center applications. Despite many previous studies on using NVM in a single machine, there remain challenges to best utilize it in a distributed data...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Proceedings of the International Conference on Distributed Computing Systems s. 92 - 103
Hlavní autori: Duan, Zhuohui, Liu, Haikun, Lu, Haodi, Liao, Xiaofei, Jin, Hai, Zhang, Yu, He, Bingsheng
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.07.2021
Predmet:
Conferences
Costs
Data centers
Distributed Shared Memory
Non-volatile Memory
Nonvolatile memory
Persistent Memory
Protocols
Random access memory
RDMA
Semantics
ISSN:2575-8411
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Byte-addressable Non-volatile Memory (NVM) technologies promise higher density and lower cost than DRAM. They have been increasingly employed for data center applications. Despite many previous studies on using NVM in a single machine, there remain challenges to best utilize it in a distributed data center environment. This paper presents Gengar, an RDMA-enabled Distributed Shared Hybrid Memory (DSHM) pool with simple programming APIs on viewing remote NVM and DRAM in a global memory space. We propose to exploit semantics of RDMA primitives to identify frequently-accessed data in the hybrid memory pool, and cache it in distributed DRAM buffers. We redesign RDMA communication protocols to reduce the bottleneck of RDMA write latency by leveraging a proxy mechanism. Gengar also supports memory sharing among multiple users with data consistency guarantee. We evaluate Gengar in a real testbed equipped with Intel Optane DC Persistent DIMMs. Experimental results show that Gengar significantly improves the performance of public benchmarks such as MapReduce and YCSB by up to 70 % compared with state-of-the-art DSHM systems.
ISSN:2575-8411
DOI:10.1109/ICDCS51616.2021.00018