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HALO: a fast and durable disk write cache using phase change memory

delete2017-08-04
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AI
Z
Zhuo Liu
王斌 封面图
王斌 (Bin Wang)
W
Weikuan Yu *
DOI:10.1007/s10586-017-1076-0delete
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摘要

摘要

En 中文
To close the increasing performance gap between disk storage and processors, flash based solid-state devices (FSSDs) have been adopted within the memory hierarchy to improve the performance of hard disk drive (HDD) based storage system. However, FSSDs still suffer from erase-before-write restriction, coarse access granularity and limited write endurance. Recently, the cutting-edge non-volatile memory technologies are merging, e.g., phase-change memory and resistive memory, which offer us new storage alternatives with faster access, byte-addressability and better endurance. In order to address the imperative data intensive computing issues, we propose to leverage PCM as disk write cache for constructing a hybrid PCM+HDD storage architecture in this paper. First, we develop a novel hash-based write caching scheme called HALO to improve both spatial and temporal locality on hard disks, thus addressing the limitations of traditional LRU caching algorithms and rendering better I/O performance. To deal with the limited durability of PCM devices and reclaim the degraded spatial locality in previous wear-leveling techniques, we further propose novel PCM wear leveling algorithms that provide effectively uniform writes while maximizing access parallelism. We have evaluated this PCM-based hybrid storage architecture using applications with a diverse set of I/O access patterns. Our experimental results demonstrate that the HALO caching scheme leads to an average reduction of 36.8% in execution time compared to the LRU caching scheme, and that the space filling curve based wear leveling extends the lifetime of PCM by a factor of 21.6.
Keyword:
PCM
Cache
Wear leveling
Hybrid storage
Cuckoo hashing
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期刊

C
Cluster Computing-The Journal of Networks Software Tools and Applications
IF:
4.1
论文数:
5.0K
被引数:
7.5K

机构

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Auburn University
学者数:
7.2K
论文数: 5.9K
被引数: 1.3W
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auburn university system
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论文数: 9.5K
被引数: 9
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