Gengar:一个基于rdma的分布式混合内存池

Zhuohui Duan, Haikun Liu, Haodi Lu, Xiaofei Liao, Hai Jin, Yu Zhang, Bingsheng He
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引用次数: 2

摘要

字节可寻址非易失性存储器(NVM)技术承诺比DRAM具有更高的密度和更低的成本。它们越来越多地用于数据中心应用程序。尽管之前有许多关于在单台机器中使用NVM的研究,但在分布式数据中心环境中最好地利用它仍然存在挑战。Gengar是一个支持rdma的分布式共享混合内存(DSHM)池,具有简单的编程api,用于在全局内存空间中查看远程NVM和DRAM。我们建议利用RDMA原语的语义来识别混合内存池中频繁访问的数据,并将其缓存在分布式DRAM缓冲区中。我们重新设计了RDMA通信协议,利用代理机制减少了RDMA写入延迟的瓶颈。Gengar还支持多用户之间的内存共享,并保证数据一致性。我们在配备英特尔Optane DC Persistent内存条的真实测试台上对Gengar进行了评估。实验结果表明,与最先进的DSHM系统相比,Gengar显著提高了MapReduce和YCSB等公共基准测试的性能,提高幅度高达70%。
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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 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.
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