ReviveNet: A Self-Adaptive Architecture for Improving Lifetime Reliability via Localized Timing Adaptation

Abstract

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.