MadFS: Per-File Virtualization for Userspace Persistent Memory Filesystems


Shawn Zhong, Chenhao Ye, Guanzhou Hu, Suyan Qu, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, and Michael Swift, University of Wisconsin–Madison


Persistent memory (PM) can be accessed directly from userspace without kernel involvement, but most PM filesystems still perform metadata operations in the kernel for security and rely on the kernel for cross-process synchronization.

We present per-file virtualization, where a virtualization layer implements a complete set of file functionalities, including metadata management, crash consistency, and concurrency control, in userspace. We observe that not all file metadata need to be maintained by the kernel and propose embedding insensitive metadata into the file for userspace management. For crash consistency, copy-on-write (CoW) benefits from the embedding of the block mapping since the mapping can be efficiently updated without kernel involvement. For cross-process synchronization, we introduce lock-free optimistic concurrency control (OCC) at user level, which tolerates process crashes and provides better scalability.

Based on per-file virtualization, we implement MadFS, a library PM filesystem that maintains the embedded metadata as a compact log. Experimental results show that on concurrent workloads, MadFS achieves up to 3.6× the throughput of ext4-DAX. For real-world applications, MadFS provides up to 48% speedup for YCSB on LevelDB and 85% for TPC-C on SQLite compared to NOVA.

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@inproceedings {285756,
author = {Shawn Zhong and Chenhao Ye and Guanzhou Hu and Suyan Qu and Andrea Arpaci-Dusseau and Remzi Arpaci-Dusseau and Michael Swift},
title = {{MadFS}: {Per-File} Virtualization for Userspace Persistent Memory Filesystems},
booktitle = {21st USENIX Conference on File and Storage Technologies (FAST 23)},
year = {2023},
isbn = {978-1-939133-32-8},
address = {Santa Clara, CA},
pages = {265--280},
url = {},
publisher = {USENIX Association},
month = feb

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