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WMAlloc: A Wear-Leveling-Aware Multi-Grained Allocator for Persistent Memory File Systems

Authors :
Wenbin Wang
Shun Nie
Chaoshu Yang
Xianzhang Chen
Duo Liu
Runyu Zhang
Source :
ICPADS
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

Emerging Persistent Memories (PMs) are promised to revolutionize the storage systems by providing fast, persistent data access on the memory bus. Therefore, persistent memory file systems are developed to achieve high performance by exploiting the advanced features of PMs. Unfortunately, the PMs have the problem of limited write endurance. Furthermore, the existing space management strategies of persistent memory file systems usually ignore this problem, which can cause that the write operations concentrate on a few cells of PM. Then, the unbalanced writes can damage the underlying PMs quickly, which seriously damages the data reliability of the file systems. However, existing wear-leveling-aware space management techniques mainly focus on improving the wear-leveling accuracy of PMs rather than reducing the overhead, which can seriously reduce the performance of persistent memory file systems. In this paper, we propose a Wear-Leveling-Aware Multi-Grained Allocator, called WMAlloc, to achieve the wear-leveling of PM while improving the performance for persistent memory file systems. WMAlloc adopts multiple heap trees to manage the unused space of PM, and each heap tree represents an allocation granularity. Then, WMAlloc allocates less-worn required blocks from the heap tree for each allocation. We implement the proposed WMAlloc in Linux kernel based on NOVA, a typical persistent memory file system. Compared with DWARM, the state-of-the-art and wear-leveling-aware space management technique, experimental results show that WMAlloc can achieve 1.52× lifetime of PM and 1.44× performance improvement on average.

Details

Database :
OpenAIRE
Journal :
2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)
Accession number :
edsair.doi...........f6e1b15f01218e4282362c59f1ecb62e
Full Text :
https://doi.org/10.1109/icpads51040.2020.00072