Delaying Crash Consistency for Building A High-Performance Persistent Memory File System

作者：Yanqi Pan, Hao Huang, Yifeng Zhang, Wen Xia, Xiangyu Zou, Cai Deng · 发表于：IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 年份：2024 · DOI：10.1109/tcad.2024.3375792 · 被引用次数：6 · 研究领域：Advanced Data Storage Technologies、Distributed systems and fault tolerance、Parallel Computing and Optimization Techniques

Persistent Memory (PM), with its low latency, byte-addressability, and non-volatility, sparks various PM file systems. Nevertheless, we observe that these file systems can waste more than 50% PM I/O bandwidth, hindering the value of PM. Our in-depth analysis reveals that this can be rooted in their strong consistency assumptions that require synchronized PM I/O for strict data integrity. Nevertheless, these I/Os, including attribute updates, space management, and journaling, are generally small, random, and fail to match with the PM I/O characteristics. We present HUNTER, a POSIX-compliant PM file system that aims to unleash PM I/O performance with strict data integrity. Our key insight is delaying crash consistency with emerging flush-on-fail (FoF) hardware. We achieve this insight by first leveraging a PM-simplified soft update mechanism to persist metadata (i.e., consistent view) in the background; while maintaining up-to-date states in DRAM (i.e., latest view) for instantaneous user responding. Compared to prior works, HUNTER carefully decouples the latest view from the consistent view, and thus, background operations will not block the foreground paths, which fully exploits soft update efficiency. Under this architecture, FoF hardware allows a residual energy window for state synchronization during system failures. However, ensuring strict data integrity is still non-trivial due to existing deficient sync mechanisms that might either hide the benefits of soft update or f...