方法证据记录
Monte Carlo Process Variation
Monte Carlo Process Variation analysis quantifies the impact of manufacturing uncertainties on circuit performance using statistical sampling. As semiconductor technology scales, process variations (gate length, oxide thickness, dopant fluctuations) create significant uncertainties in delay, power, and leakage. Monte Carlo methods sample the random variation space, enabling statistical characterization of yield, timing margins, and reliability. Essential for modern technology nodes.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Monte Carlo Analysis of Semiconductor Process Variations
分类方法记录 · process-pipeline / electrical-engineering
- Fishman, G. S. (1996). Monte Carlo: Concepts, Algorithms, and Applications. Springer-Verlag. · DOI 10.1007/978-1-4757-2553-7
- Nassif, S. R. (2003). Modeling and analysis of manufacturing variations. In Proc. CICC (pp. 223-228). IEEE. · DOI 10.1109/cicc.2001.929760
- Agarwal, A., Blaauw, D., Zolotov, V., & Sundareswaran, S. (2005). Statistical timing analysis with dual-Vth devices. IEEE Transactions on VLSI Systems, 13(3), 319-328. · URL
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