Multi-Granularity Shadow Paging with NVM Write Optimization for Crash-Consistent Memory-Mapped I/O

Hongchao Du, Qiao Li, Riwei Pan, Tei-Wei Kuo, Chun Jason Xue

Abstract: The complex software stack has become the performance bottleneck of the system with high-speed Non-Volatile Memory (NVM). Memory-mapped I/O (MMIO) could avoid the long-stack overhead by bypassing the kernel, but the performance is limited by existing crash-resilient mechanisms. We propose a Multi-Granularity Shadow Paging (MGSP) strategy, which smartly utilizes the redo and undo logs as shadow logs to provide a light-weight crash-resilient mechanism for MMIO. In addition, a multi-granularity strategy is designed to provide high-performance updating and locking for reducing runtime overhead, where strong consistency is preserved with a lockfree metadata log. Experimental results show that the proposed MGSP achieves 1.1 ~ 4.21× performance improvement with write and 2.56 ~ 3.76× improvement with multi-threads write compared with the underlying file system. For SQLite, MGSP can improve the database performance by 29.4% for Mobibench and 36.5% for TPCC, on average.