Chung-Kai Lin

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Using simulation to assess the impacts of various reliability mechanisms to circuit performance has become prevail for advanced technologies due to smaller headroom (=Vdd-Vth) and less design margins. This paper reviews existing circuit aging simulation approaches with focus on TMI. The limitations of aging models are also discussed so that reliability(More)
Process variation has become a serious concern in nanometer technologies. Designs with competitive margins rely on well-characterized statistical models, which must predict the magnitude and scalability of variability accurately. In this paper, we propose a novel approach in creating the statistical models, which tracks the global variation correlation(More)
A comprehensive variation model is critical to achieve both competitive design and manufacturing yield in advanced technologies. Conventionally, as long as FEOL (front end of line) statistical model is appropriate, BEOL (back end of line) variations given by lumping multiple variation sources into few corners is enough to achieve reliable simulation(More)
In this paper, we discuss how to implement the self heating and aging models with TMI. Various examples about self heating and aging simulations with TMI methodology are shown in this paper. Without trading-off the accuracy, the one with proposed TMI approach for self heating simulations takes much shorter simulation time.
A high-sigma corner model derived from Monte Carlo simulation with a novel sampling algorithm is presented. Compared with the traditional Monte Carlo simulation approach, the simulation effort and computational resource is greatly reduced. This methodology can be applied to create application-specific corner model for different design spec leading to more(More)
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