In-memory ordered key-value stores are an important building block in modern distributed applications. We present Honeycomb, a hybrid software-hardware system for accelerating read-dominated workloads on ordered key-value stores that provides linearizability for all operations including scans. Honeycomb stores a B-Tree in host memory, and executes SCAN and GET on an FPGA-based SmartNIC, and PUT, UPDATE and DELETE on the CPU. This approach enables large stores and simplifies the FPGA implementation but raises the challenge of data access and synchronization across the slow PCIe bus. We describe how Honeycomb overcomes this challenge with careful data structure design, caching, request parallelism with out-of-order request execution, wait-free read operations, and batching synchronization between the CPU and the FPGA. For read-heavy YCSB workloads, Honeycomb improves the throughput of a state-of-the-art ordered key-value store by at least 1.8x. For scan-heavy workloads inspired by cloud storage, Honeycomb improves throughput by more than 2x. The cost-performance, which is more important for large-scale deployments, is improved by at least 1.5x on these workloads.

翻译：摘要：内存有序键值存储是现代分布式应用中的重要构建模块。我们提出Honeycomb，一种用于加速有序键值存储上读密集型工作负载的混合软硬件系统，它能为包括扫描在内的所有操作提供线性一致性。Honeycomb在主机内存中存储B树，并在基于FPGA的智能网卡上执行SCAN和GET操作，而在CPU上执行PUT、UPDATE和DELETE操作。这种设计支持大规模存储并简化了FPGA实现，但带来了通过慢速PCIe总线进行数据访问和同步的挑战。我们描述了Honeycomb如何通过精心设计数据结构、缓存、乱序请求执行的请求并行、无等待读操作以及CPU与FPGA之间的批量同步来克服这一挑战。对于读密集型的YCSB工作负载，Honeycomb将最先进的有序键值存储的吞吐量提升了至少1.8倍。对于受云存储启发的扫描密集型工作负载，Honeycomb将吞吐量提升了超过2倍。对于大规模部署更重要的性价比，在这些工作负载上至少提升了1.5倍。