Memory-disaggregated key-value (KV) stores suffer from a severe performance bottleneck due to their I/O redundancy issues. A huge amount of redundant I/Os are generated when synchronizing concurrent data accesses, making the limited network between the compute and memory pools of DM a performance bottleneck. We identify the root cause for the redundant I/O lies in the mismatch between the optimistic synchronization of existing memory-disaggregated KV stores and the highly concurrent workloads on DM. In this paper, we propose to boost memory-disaggregated KV stores with pessimistic synchronization. We propose CIDER, a compute-side I/O optimization framework, to verify our idea. CIDER adopts a global write-combining technique to further reduce cross-node redundant I/Os. A contention-aware synchronization scheme is designed to improve the performance of pessimistic synchronization under low contention scenarios. Experimental results show that CIDER effectively improves the throughput of state-of-the-art memory-disaggregated KV stores by up to $6.6\times$ under the YCSB benchmark.

翻译：内存解耦型键值存储系统因输入/输出冗余问题面临严重的性能瓶颈。在同步并发数据访问时产生大量冗余I/O，使计算池与内存池之间的有限网络成为性能瓶颈。研究发现，冗余I/O的根本原因在于现有内存解耦键值存储采用的乐观同步机制与DM环境下的高并发负载存在不匹配。本文提出采用悲观同步技术来提升内存解耦键值存储性能，并设计计算端I/O优化框架CIDER验证该思路。CIDER采用全局写合并技术进一步减少跨节点冗余I/O，同时设计基于竞争感知的同步方案，在低竞争场景下改善悲观同步性能。实验结果表明，在YCSB基准测试中，CIDER可将最先进的内存解耦键值存储的吞吐量提升至$6.6\times$。