Title | ||
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SCOR-KV: SIMD-Aware Client-Centric and Optimistic RDMA-Based Key-Value Store for Emerging CPU Architectures |
Abstract | ||
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Modern distributed key-value store-based applications rely on bulk-read operations like 'Multi-Get' (MGet) to accelerate their data serving phase. While state-of-the-art database systems employ SIMD-based techniques to optimize data-parallel operations on their in-memory structures, such as hash-tables, they have not been adapted into high-performance RDMA-accelerated key-value (KV) stores. In this paper, we present a holistic approach to designing high-performance SIMD-aware KV stores for emerging multi-core CPU architectures. Towards this, we first perform an in-depth study of the opportunities and challenges involved in leveraging AVX-512 vectorization-based parallel hash table designs with a state-of-the-art high-performance key-value store like RDMA-Memcached. Based on this, we propose a SIMD-Aware Client-Centric and Optimistic RDMA-based Key-Value Store, SCOR-KV, that optimally exploits 'RDMA+SIMD' to accelerate read-heavy MGet operations. SCOR-KV presents an SIMD-conscious KV store friendly hash table layout, that leverages the vertically vectorized N-way cuckoo hash table design with optimistic KV pair lookup schemes. To complement this, we propose RDMA-optimized SIMD-aware MGet communication protocols that offload the server-side pre-/post-processing overheads to the client, while enabling optimal end-to-end performance. Our performance evaluations over the latest Intel Skylake CPUs and IB EDR interconnects show that our proposed SCOR-KV can achieve up to 3.7-8.6x improvement in server-side Get throughput. Through our SIMD-aware RDMA schemes, SCOR-KV can also improve Multi-Get latencies for read-heavy YCSB workloads by about 2.2x, as compared to the RDMA-Memcached design running over the state-of-the-art CPU-optimized MemC3 hash table design. |
Year | DOI | Venue |
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2019 | 10.1109/HiPC.2019.00040 | 2019 IEEE 26th International Conference on High Performance Computing, Data, and Analytics (HiPC) |
Keywords | Field | DocType |
CPU-SIMD, Key-Value Store, RDMA, AVX-512 | Computer architecture,Computer science,Parallel computing,SIMD,Vectorization (mathematics),Remote direct memory access,Associative array,Throughput,Cuckoo hashing,Hash table,Communications protocol | Conference |
ISSN | ISBN | Citations |
1094-7256 | 978-1-7281-4536-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dipti Shankar | 1 | 120 | 10.71 |
Xiaoyi Lu | 2 | 602 | 60.53 |
Dhabaleswar K. Panda | 3 | 5366 | 446.70 |