SCOR-KV: SIMD-Aware Client-Centric and Optimistic RDMA-Based Key-Value Store for Emerging CPU Architectures

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.