Forca: Fast and Atomic Remote Direct Access to Persistent Memory

Abstract

For promising performance boost, recent trends of modern data centers tend to use Persistent Memory (PM) as storage and utilize the one-sided feature of Remote Direct Memory Access (RDMA) to directly access PM for I/O requests. However, accessing PM through one-sided RDMA faces two challenges: one-sided data races and remote data crash consistency. Existing systems that employ server-bypass mechanism either abandon server-bypass write to avoid the challenges at the cost of extra server loads, or support both server-bypass read/write through inefficient concurrency control without ensuring remote crash consistency. In this paper, we propose a novel server-bypass RDMA-to-PM framework, named Forca, to provide high concurrency and guarantee remote crash consistency at the same time. In Forca, we design an optimized log-structured mechanism to eliminate in-place updates, removing race conditions of one-sided RDMA and providing atomicity for each update simultaneously. We implement Forca as a generic module to support server-bypass RDMA to PM, and conduct experiments on a Forca-based key-value store called ForcaKV. The experiments show that Forca achieves higher throughput than state-of-the-art techniques by up to 1.4x under high concurrency scenarios, and its crash consistency mechanism incurs only 14.7%-19.1% time overhead.