A Host-CSD Collaborative Framework for High-Performance LSM-Based KV Stores

LSM-based key-value stores are widely used due to their write efficiency and scalability. However, their background compaction process requires substantial data movement between the host and storage devices, resulting in inefficient resource usage, frequent write stalls, and degraded overall throughput. Existing optimizations fail to address the performance bottlenecks caused by excessive system interconnect traffic. Although in-storage computing offers a promising way to mitigate data transfer overhead, prior works typically offload all compaction tasks blindly to computational storage devices. Our preliminary experiments show that such naive offloading leads to performance inefficiency due to CSD resource constraints. In this work, we propose CSD-CoKV + , a host-CSD collaborative framework that enables efficient compaction acceleration for LSM-based KV stores. Specifically, we design a semantic-aware offloader to selectively dispatch suitable compaction jobs to CSDs, together with a lightweight FPGA-based compaction kernel for efficient in-storage execution under constrained device resources. In addition, we develop a range-partitioned data organization with two-level load balancing to preserve locality and improve scalability across CSD arrays, and further introduce a host-device hierarchical cache to better exploit device-level locality in the read path. Evaluations on a real SmartSSD-based prototype show that, with the default host-only baseline, CSD-CoKV + improves write throughput by up to 2.26 × and boosts compaction throughput by up to 3.42 ×, while improving read throughput by up to 28.5%.