Affiliation:
1. Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University and School of Computer and Information, Hohai University
2. School of Computer and Information, Hohai University
3. Intel Labs
4. State Key Laboratory for Novel Software Technology, Nanjing University and Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University and School of Computer and Information, Hohai University
Abstract
Emerging NUMA/CXL-based tiered memory systems with heterogeneous memory devices such as DRAM and NVMM deliver ultrafast speed, large capacity, and data persistence all at once, offering great promise to high-performance in-memory key-value stores. To fully unleash the performance potential of such memory systems, this paper presents BonsaiKV, a key-value store that makes the best use of different components in a tiered memory system. The core of BonsaiKV is a tri-layer hierarchical storage architecture that separates data indexing, persistence, and scalability from each other and realizes each of them within a specialized software-hardware layer. We design BonsaiKV with a set of novel techniques, including collaborative tiered indexing, NVMM congestion control mechanisms, fine-grained data striping, and NUMA-aware data management, to leverage hardware strengths and tackle device deficiencies. We compare BonsaiKV with state-of-the-art NVMM-optimized key-value stores and persistent index structures using a variety of YCSB workloads. Evaluation results demonstrate that BonsaiKV outperforms others by up to 7.69×, 19.59×, and 12.86× in read-, write- and scan-intensive scenarios, respectively.
Publisher
Association for Computing Machinery (ACM)
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