Software enabled wear-leveling for hybrid PCM main memory on embedded systems

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

  • Affiliations:
  • University of Texas at Dallas, Richardson, TX;Chongqing University, Chongqing, China;City University of Hong Kong, Tat Chee Ave, Kowloon, Hong Kong;University of Texas at Dallas, Richardson, TX;University of Texas at Dallas, Richardson, TX and Chongqing University, Chongqing, China

  • Venue:
  • Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2013

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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.