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A novel sample reuse methodology for fast statistical simulations with applications to manufacturing variability

机译:一种新颖的样本重用方法,可用于快速统计仿真并应用于制造变异性

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摘要

In this paper we propose a highly efficient statistical simulation methodology based on sample reuse. In the event of design re-centering, multiple manufacturing variability corners, or statistical sensitivity analysis the methodology enables design yield estimations at no additional cost to the reference center analysis. Sample points from the reference center statistical simulation can be utilized to estimate the yield at multiple neighboring centers. The capabilities of the methodology are further extended by projecting the new center onto the critical fail/sampling direction of the reference simulation. This improves the accuracy of the estimate and widens the scope of application. Theoretical applications and analysis of state of the art memory designs indicate excellent yield estimate matching and several orders of magnitude of speedup due to sample reuse.
机译:在本文中,我们提出了一种基于样本重用的高效统计仿真方法。在进行设计重新定中心,多个制造可变性拐角或统计敏感性分析的情况下,该方法可以在不增加参考中心分析成本的情况下进行设计成品率估算。参考中心统计模拟的采样点可用于估计多个相邻中心的产量。通过将新的中心投影到参考模拟的关键失效/采样方向上,可以进一步扩展该方法的功能。这提高了估计的准确性并扩大了应用范围。理论上的应用和对最先进的存储器设计的分析表明,由于样品的重复使用,可以实现出色的产量估算匹配和几个数量级的加速。

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