Optimization of importance sampling Monte Carlo using consecutive mean-shift method and its application to SRAM dynamic stability analysis

Takeshi Kida, Y. Tsukamoto, Y. Kihara
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引用次数: 17

Abstract

With the scaling of MOSFET dimensions and the lowering of supply voltage, more precise estimation of minimum operating voltage (Vmin) of SRAM at 6-sigma level is needed. In this paper, we propose a method based on the importance sampling (IS) Monte Carlo simulation to elaborately predict Vmin for future technology node below 22 nm generation. By executing Monte Carlo (MC) simulation with consecutive mean-shift method we propose, it is shown that the most probable failure point (MPFP) is effectively and steadily derived within 0.01σ accuracy without depending on the way of random number generation. The proposed method is applied to static and dynamic behaviors of SRAM. Through the comparison with the results obtained by conventional IS method, we clarify that the method proposed is more suitable for future SRAM characterization.
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基于连续均值移位法的重要抽样蒙特卡罗优化及其在SRAM动态稳定性分析中的应用
随着MOSFET尺寸的缩小和电源电压的降低,需要更精确地估计SRAM在6 σ级的最小工作电压(Vmin)。本文提出了一种基于重要性采样(IS)蒙特卡罗模拟的方法来精细预测未来22 nm以下技术节点的Vmin。通过蒙特卡罗(MC)仿真,证明了最可能失效点(MPFP)在0.01σ的精度范围内是有效且稳定的,而不依赖于随机数生成的方式。将该方法应用于SRAM的静态和动态行为。通过与传统IS方法所得结果的比较,我们阐明了所提出的方法更适合未来SRAM的表征。
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