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

Persistent memory (PM), with its low-latency, byte-addressability, and nonvolatility, 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 nontrivial due to existing deficient sync mechanisms that might either hide the benefits of soft update or fail to flush all states during the FoF window. We propose collaborated synchronization that bridges the two views to minimize PM I/O to address the issue. Our extensive experiments show that HUNTER can achieve 1.35–
$7.51\times $
I/O throughput compared to existing PM file systems. Under the strict workload configurations, HUNTER outperforms the fastest PM file system by 72%–122%.