Efficient multi-grained wear leveling for inodes of persistent memory file systems
2020 57th ACM/IEEE Design Automation Conference (DAC), 2020•ieeexplore.ieee.org
Existing persistent memory file systems usually store inodes in fixed locations, which ignores
the external and internal imbalanced wears of inodes on the persistent memory (PM).
Therefore, the PM for storing inodes can be easily damaged. Existing solutions achieve low
accuracy of wear-leveling with high-overhead data migrations. In this paper, we propose a
Lightweight and Multi-grained Wear-leveling Mechanism, called LMWM, to solve these
problems. We implement the proposed LMWM in Linux kernel based on NOVA, a typical …
the external and internal imbalanced wears of inodes on the persistent memory (PM).
Therefore, the PM for storing inodes can be easily damaged. Existing solutions achieve low
accuracy of wear-leveling with high-overhead data migrations. In this paper, we propose a
Lightweight and Multi-grained Wear-leveling Mechanism, called LMWM, to solve these
problems. We implement the proposed LMWM in Linux kernel based on NOVA, a typical …
Existing persistent memory file systems usually store inodes in fixed locations, which ignores the external and internal imbalanced wears of inodes on the persistent memory (PM). Therefore, the PM for storing inodes can be easily damaged. Existing solutions achieve low accuracy of wear-leveling with high-overhead data migrations. In this paper, we propose a Lightweight and Multi-grained Wear-leveling Mechanism, called LMWM, to solve these problems. We implement the proposed LMWM in Linux kernel based on NOVA, a typical persistent memory file system. Compared with MARCH, the state-of-theart wear-leveling mechanism for inode table, experimental results show that LMWM can improve 2.5× lifetime of PM and 1.12× performance, respectively.
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