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An approach for digital Circuit Error/Reliability Propagation Analysis based on Conditional Probability

机译:一种基于条件概率的数字电路误差/可靠性传播分析方法

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The continuous transistor scaling and extremely lower power constraints in modern VLSI chips can potentially supersede the benefits of the technology shrinking due to reliability issues. Due to external aggression factors, e.g., radiation and temperature gradients, the CMOS devices flawless functioning cannot be guaranteed any more. Thus, design time Integrated Circuits (ICs) reliability assessment is now turning out to be a mandatory step in the IC design flow. In this work, we present a novel CAD analytical error/reliability propagation analysis technique called Conditional Probabilistic Error/Reliability Propagation Analysis (CPERPA) algorithm. CPERPA efficiently resolves reliability related correlations including reconvergent fanouts and related errors, using a condition algorithm originating from the conditional probability theory, which promotes the accuracy at the expense of relatively low complexity enhancement. Experimental results on several benchmark circuits demonstrate the accuracy and the simulation time advantages of our approach when compared to Monte-Carlo simulations. The results obtained with the proposed CPERPA framework are within 3% average error and up to 1000 times faster when compared to Monte-Carlo simulations.
机译:现代VLSI芯片中的连续晶体管缩放和极低的功率约束可能使技术因可靠性问题而萎缩的益处。由于外部侵略因素,例如辐射和温度梯度,CMOS器件无瑕疵的功能不能再保证。因此,设计时间集成电路(ICS)可靠性评估现已成为IC设计流程中的强制性步骤。在这项工作中,我们提出了一种新的CAD分析误差/可靠性传播分析技术,称为条件概率误差/可靠性传播分析(CPERPA)算法。 CPEPA有效地解决了包括源自条件概率理论的条件算法的可靠性相关的相关性,包括重构扇出和相关误差,该条件算法促进了牺牲了相对低的复杂性增强的准确性。与Monte-Carlo仿真相比,若干基准电路上的实验结果展示了我们方法的准确性和模拟时间优势。与暗中Carlo模拟相比,用拟议的CPPA框架获得的结果在3%的平均误差范围内,速度快于1000倍。

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