Predictive Technology Model for Nano-CMOS Design Exploration
Predictive Technology Model for Nano-CMOS Design Exploration
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DOI：
10.1145/1229175.1229176
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发表时间：
2007-04-01
影响因子：
2.2
通讯作者：
Cao, Yu
中科院分区：
文献类型：
--
作者：
Zhao, Wei;Cao, Yu
预测MOSFET模型对于早期电路设计研究至关重要。在这项工作中，开发了新一代的预测技术模型（PTM），涵盖了新兴的物理效应和替代结构，如双栅器件（即FinFET）。基于物理模型和前期硅数据，在130 ~ 32nm技术节点上成功生成了本体和双栅器件的PTM，有效通道长度降至13nm。通过只调整10个主要参数，PTM可以很容易地定制，以覆盖广泛的过程不确定性。PTM预测的准确性通过已发表的硅数据得到了全面验证：NMOS和PMOS的电流误差都在10%以下。此外，新的PTM正确地捕获了纳米范围内的工艺灵敏度。PTM可在线访问http://www.eas.asu.edu/similar to PTM。
A predictive MOSFET model is critical for early circuit design research. In this work, a new generation of Predictive Technology Model (PTM) is developed, covering emerging physical effects and alternative structures, such as the double-gate device (i.e., FinFET). Based on physical models and early stage silicon data, PTM of bulk and double-gate devices are successfully generated from 130nm to 32nm technology nodes, with effective channel length down to 13nm. By tuning only ten primary parameters, PTM can be easily customized to cover a wide range of process uncertainties. The accuracy of PTM predictions is comprehensively verified with published silicon data: the error of the current is below 10% for both NMOS and PMOS. Furthermore, the new PTM correctly captures process sensitivities in the nanometer regime. PTM is available online at http://www.eas.asu.edu/similar to ptm.