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Rapid Estimation of the Probability of SRAM Failure due to MOS Threshold Variations

机译:由于MS阈值变化而快速估计SRAM故障概率

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Accurate estimation of the effects of threshold variations, in particular yield loss, is crucial during the design of robust SRAM cells and memory arrays in deep submicron technologies. We present an efficient technique to calculate yield loss due to access-time, static noise margin, etc., related failures. Our method does not rely on Monte-Carlo techniques; instead, it finds the boundary in Vt (threshold voltage) parameter space between success and failure regions and uses quick geometrical calculations to find the yield. The Vt boundary curve is found efficiently via an Euler-Newton curve tracing technique, adapted from mixed-signal/RF simulation, that guides detailed SPICE-level simulation with accurate MOS device models. We compare and validate the new method against Monte-Carlo style yield estimation, obtaining superior accuracies and speedups of more than 10脳.
机译:精确估计阈值变化的效果,特别是屈服损失在深度亚微米技术的鲁棒SRAM细胞和内存阵列的设计期间至关重要。我们提出了一种有效的技术来计算由于访问时间,静态噪声边缘等相关的屈服损失,相关的故障。我们的方法不依赖于Monte-Carlo技术;相反,它发现了成功和故障区域之间的VT(阈值电压)参数空间中的边界,并使用快速几何计算来找到产量。 V T 边界曲线通过euler-newton曲线跟踪技术有效地发现,适用于混合信号/射频仿真,将详细的SPICE级模拟与精确的MOS设备模型引导。我们比较并验证蒙特卡罗风格产量估计的新方法,获得卓越的精度和超过10‰的加速。

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