Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems

Jingtong Hu; Qingfeng Zhuge; Chun Jason Xue; Wei-Che Tseng; Edwin H.-M. Sha

doi:10.7873/DATE.2013.131

Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems

Jingtong Hu, Qingfeng Zhuge, Chun Jason Xue, Wei-Che Tseng, Edwin H.-M. Sha

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

70 Citations (Scopus)

Abstract

Phase Change Memory (PCM) is a promising DRAM replacement in embedded systems due to its attractive characteristics. However, relatively low endurance has limited its practical applications. In this paper, in additional to existing hardware level optimizations, we propose software enabled wear-leveling techniques to further extend PCM's lifetime when it is adopted in embedded systems. A polynomial-time algorithm, the Software Wear-Leveling (SWL) algorithm, is proposed in this paper to achieve wear-leveling without hardware overhead. According to the experimental results, the proposed technique can reduce the number of writes on the most-written bits by more than 80% when compared with a greedy algorithm, and by around 60% when compared with the existing Optimal Data Allocation (ODA) algorithm with under 6% memory access overhead. © 2013 EDAA.

Original language	English
Title of host publication	2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Publisher	IEEE
Pages	599-602
ISBN (Electronic)	978-3-9815370-0-0
ISBN (Print)	978-1-4673-5071-6
DOIs	https://doi.org/10.7873/DATE.2013.131
Publication status	Published - Mar 2013
Event	16th Design, Automation and Test in Europe Conference and Exhibition (DATE 2013) - Grenoble, France Duration: 18 Mar 2013 → 22 Mar 2013

Publication series

Name	Design, Automation and Test in Europe Conference and Exhibition
ISSN (Print)	1530-1591
ISSN (Electronic)	1530-1591

Conference

Conference	16th Design, Automation and Test in Europe Conference and Exhibition (DATE 2013)
Place	France
City	Grenoble
Period	18/03/13 → 22/03/13

Funding

This work is partially supported by NSF CNS-1015802, Texas NHARP 009741-0020-2009, HK GRF 123609, NSFC 61173014, National 863 Program 2013AA013202 and grants from the Research Grants Council of the Hong Kong Special Administrative Region, China [Project No. CityU 123811 and 123210].

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RGC-funded

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10.7873/DATE.2013.131

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@inproceedings{b99efaa643664452b6f144a4d0e5fd4c,

title = "Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems",

abstract = "Phase Change Memory (PCM) is a promising DRAM replacement in embedded systems due to its attractive characteristics. However, relatively low endurance has limited its practical applications. In this paper, in additional to existing hardware level optimizations, we propose software enabled wear-leveling techniques to further extend PCM's lifetime when it is adopted in embedded systems. A polynomial-time algorithm, the Software Wear-Leveling (SWL) algorithm, is proposed in this paper to achieve wear-leveling without hardware overhead. According to the experimental results, the proposed technique can reduce the number of writes on the most-written bits by more than 80% when compared with a greedy algorithm, and by around 60% when compared with the existing Optimal Data Allocation (ODA) algorithm with under 6% memory access overhead. {\textcopyright} 2013 EDAA.",

author = "Jingtong Hu and Qingfeng Zhuge and Xue, {Chun Jason} and Wei-Che Tseng and Sha, {Edwin H.-M.}",

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Hu, J, Zhuge, Q, Xue, CJ, Tseng, W-C & Sha, EH-M 2013, Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems. in 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE)., 6513577, Design, Automation and Test in Europe Conference and Exhibition, IEEE, pp. 599-602, 16th Design, Automation and Test in Europe Conference and Exhibition (DATE 2013), Grenoble, France, 18/03/13. https://doi.org/10.7873/DATE.2013.131

Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems. / Hu, Jingtong; Zhuge, Qingfeng; Xue, Chun Jason et al.
2013 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2013. p. 599-602 6513577 (Design, Automation and Test in Europe Conference and Exhibition).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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N2 - Phase Change Memory (PCM) is a promising DRAM replacement in embedded systems due to its attractive characteristics. However, relatively low endurance has limited its practical applications. In this paper, in additional to existing hardware level optimizations, we propose software enabled wear-leveling techniques to further extend PCM's lifetime when it is adopted in embedded systems. A polynomial-time algorithm, the Software Wear-Leveling (SWL) algorithm, is proposed in this paper to achieve wear-leveling without hardware overhead. According to the experimental results, the proposed technique can reduce the number of writes on the most-written bits by more than 80% when compared with a greedy algorithm, and by around 60% when compared with the existing Optimal Data Allocation (ODA) algorithm with under 6% memory access overhead. © 2013 EDAA.

AB - Phase Change Memory (PCM) is a promising DRAM replacement in embedded systems due to its attractive characteristics. However, relatively low endurance has limited its practical applications. In this paper, in additional to existing hardware level optimizations, we propose software enabled wear-leveling techniques to further extend PCM's lifetime when it is adopted in embedded systems. A polynomial-time algorithm, the Software Wear-Leveling (SWL) algorithm, is proposed in this paper to achieve wear-leveling without hardware overhead. According to the experimental results, the proposed technique can reduce the number of writes on the most-written bits by more than 80% when compared with a greedy algorithm, and by around 60% when compared with the existing Optimal Data Allocation (ODA) algorithm with under 6% memory access overhead. © 2013 EDAA.

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Software Enabled Wear-Leveling for Hybrid PCM Main Memory on Embedded Systems

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