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ReviveNet: A Self-Adaptive Architecture for Improving Lifetime Reliability via Localized Timing Adaptation
September 2011 (vol. 60 no. 9)
pp. 1219-1232
Guihai Yan, Chinese Academy of Sciences, Institute of Computing Technology, Beijing
Yinhe Han, Chinese Academy of Sciences, Beijing
Xiaowei Li, Chinese Academy of Sciences, Institute of Computing Technology, Beijing
The aggressive technology scaling poses serious challenges to lifetime reliability. A parament challenge comes from a variety of aging mechanisms that can cause gradual performance degradation of circuits. Prior work shows that such progressive degradation can be reliably detected by dedicated aging sensors, which provides a good foundation for proposing a new scheme to improve lifetime reliability. In this paper, we propose ReviveNet, a hardware-implemented aging-aware and self-adaptive architecture. Aging awareness is realized by deploying dedicated aging sensors, and self-adaptation is achieved by employing a group of synergistic agents. Each agent implements a localized timing adaptation mechanism to tolerate aging-induced delay on critical paths. On the evaluation, a reliability model based on widely used weibull distribution is presented. Experimental results show that, without compromising with any nominal architectural performance, ReviveNet can improve the Mean-Time-To-Failure by up to 48.7 percent, at the expense of 9.5 percent area overhead and small power increase.

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Index Terms:
Lifetime reliability, self-adaptive, aging sensor, timing adaptation, NBTI.
Citation:
Guihai Yan, Yinhe Han, Xiaowei Li, "ReviveNet: A Self-Adaptive Architecture for Improving Lifetime Reliability via Localized Timing Adaptation," IEEE Transactions on Computers, vol. 60, no. 9, pp. 1219-1232, Sept. 2011, doi:10.1109/TC.2011.33
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