An efficient wear-leveling-aware multi-grained allocator for persistent memory file systems一种磨损感知的持久化内存文件系统高效多粒度分配器

被引:0
作者
Zhiwang Yu
Runyu Zhang
Chaoshu Yang
Shun Nie
Duo Liu
机构
[1] Guizhou University,State Key Laboratory of Public Big Data, College of Computer Science and Technology
[2] Chongqing University,College of Computer Science
来源
Frontiers of Information Technology & Electronic Engineering | 2023年 / 24卷
关键词
File system; Persistent memory; Wear-leveling; Multi-grained allocator; TP212; 文件系统; 持久化内存; 磨损均衡; 多粒度分配器;
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暂无
中图分类号
学科分类号
摘要
Persistent memory (PM) file systems have been developed to achieve high performance by exploiting the advanced features of PMs, including nonvolatility, byte addressability, and dynamic random access memory (DRAM) like performance. Unfortunately, these PMs suffer from limited write endurance. Existing space management strategies of PM file systems can induce a severely unbalanced wear problem, which can damage the underlying PMs quickly. In this paper, we propose a Wear-leveling-aware Multi-grained Allocator, called WMAlloc, to achieve the wear leveling of PMs while improving the performance of file systems. WMAlloc adopts multiple min-heaps to manage the unused space of PMs. Each heap represents an allocation granularity. Then, WMAlloc allocates less-worn blocks from the corresponding min-heap for allocation requests. Moreover, to avoid recursive split and inefficient heap locations in WMAlloc, we further propose a bitmap-based multi-heap tree (BMT) to enhance WMAlloc, namely, WMAlloc-BMT. We implement WMAlloc and WMAlloc-BMT in the Linux kernel based on NOVA, a typical PM file system. Experimental results show that, compared with the original NOVA and dynamic wear-aware range management (DWARM), which is the state-of-the-art wear-leveling-aware allocator of PM file systems, WMAlloc can, respectively, achieve 4.11× and 1.81× maximum write number reduction and 1.02× and 1.64× performance with four workloads on average. Furthermore, WMAlloc-BMT outperforms WMAlloc with 1.08× performance and achieves 1.17× maximum write number reduction with four workloads on average.
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页码:688 / 702
页数:14
相关论文
共 18 条
[1]  
Liu D(2017)Durable and energy efficient in-memory frequent-pattern mining IEEE Trans Gomput-Aided Des Integr Girc Syst 36 2003-2016
[2]  
Lin Y(2016)WOM-code solutions for low latency and high endurance in phase change memory IEEE Trans Comput 65 1025-1040
[3]  
Huang PC(2011)Security Refresh: protecting phase-change memory against malicious wear out IEEE Micro 31 119-127
[4]  
Palangappa PM(2016)A new design of in-memory file system based on file virtual address framework IEEE Trans Comput 65 2959-2972
[5]  
Li JY(2016)Filebench: a flexible framework for file system benchmarking Login 41 6-12
[6]  
Mohanram K(2018)DWARM: a wear-aware memory management scheme for in-memory file systems Fut Gener Comput Syst 88 1-15
[7]  
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