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New Generation of Predictive Technology Model for Sub-45 nm Early Design Exploration

机译:适用于45纳米以下早期设计探索的新一代预测技术模型

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摘要

A predictive MOSFET model is critical for early circuit design research. To accurately predict the characteristics of nanoscale CMOS, emerging physical effects, such as process variations and correlations among model parameters, must be included. In this paper, a new generation of predictive technology model (PTM) is developed to accomplish this goal. Based on physical models and early-stage silicon data, the PTM of bulk CMOS is successfully generated for 130- to 32-nm technology nodes, with an Leff of as low as 13 nm. The accuracy of PTM predictions is comprehensively verified: The error of I on is below 10% for both n-channel MOS and p-channel MOS. By tuning only ten primary parameters, the PTM can be easily customized to cover a wide range of process uncertainties. Furthermore, the new PTM correctly captures process sensitivities in the nanometer regime, particularly the interactions among Leff, Vth, mobility, and saturation velocity. A website has been established for the release of PTM: http://www.eas.asu.edu/~ptm
机译:预测性MOSFET模型对于早期电路设计研究至关重要。为了准确地预测纳米级CMOS的特性,必须包括新兴的物理效应,例如工艺变化和模型参数之间的相关性。在本文中,开发了新一代的预测技术模型(PTM)以实现此目标。基于物理模型和早期硅数据,已成功为130至32 nm技术节点生成了批量CMOS的PTM,其Leff低至13 nm。 PTM预测的准确性得到了全面验证:n沟道MOS和p沟道MOS的I on误差均低于10%。通过仅调整十个主要参数,可以轻松定制PTM,以涵盖各种过程不确定性。此外,新的PTM可以正确捕获纳米级的工艺灵敏度,尤其是Leff,Vth,迁移率和饱和速度之间的相互作用。已经建立了一个发布PTM的网站:http://www.eas.asu.edu/~ptm

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