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Ring oscillators yield analysis: Improving Monte Carlo models with optimized clustering methods
International Journal of Circuit Theory and Applications ( IF 2.3 ) Pub Date : 2021-04-12 , DOI: 10.1002/cta.3019
Sébastien Lalléchère 1 , Zhifei Xu 2 , Jamel Nebhen 3 , Fayu Wan 4 , Blaise Ravelo 4
Affiliation  

The aim of this article is to demonstrate the interest of the optimized clustering method (OCM) when dealing with the yield analysis of ring oscillators, given uncertain assumptions over inputs. Indeed, the complementary metal–oxide semiconductor (CMOS) integrated circuit domain is facing a major challenge since these devices are subjected to noticeable fluctuations (mostly due to transistor constant scaling down at sub-micron sizes), with utmost expectations regarding their performances (e.g., for digital circuits). Whether the classical approach requires use of Monte Carlo methods coupled with classical circuit solver (e.g., Spice and/or transistor model), the natural complexity of systems and varying inputs needs to provide alternative techniques, such as OCM. The foundations of the method and its efficiency will be presented and illustrated through ring oscillator applications.

中文翻译:

环形振荡器产量分析:使用优化的聚类方法改进 Monte Carlo 模型

本文的目的是展示优化聚类方法 (OCM) 在处理环形振荡器的产量分析时的兴趣,给定对输入的不确定假设。事实上,互补金属氧化物半导体 (CMOS) 集成电路领域正面临着重大挑战,因为这些器件会受到显着的波动(主要是由于晶体管在亚微米尺寸下不断缩小),对其性能抱有最大的期望(例如,用于数字电路)。无论经典方法是否需要使用蒙特卡罗方法与经典电路求解器(例如 Spice 和/或晶体管模型)相结合,系统的自然复杂性和不同的输入需要提供替代技术,例如 OCM。
更新日期:2021-04-12
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