Large-Scale Analog/RF Performance Modeling by Statistical Regression

摘要：

In this paper,we introduce several large-scale modeling techniques to analyze the high-dimensional,strongly-nonlinear performance variability observed in nanoscale manufacturing technologies. Our goal is to solve a large number of (e.g.,104~106) model coefficients from a small set of (e.g.,102~103) sampling points without over-fitting. This is facilitated by exploiting the underlying sparsity of model coefficients. Our circuit example designed in a commercial 65nm process demonstrates that the proposed techniques achieve 25x speedup compared with the traditional response surface modeling.

关键词： Process Variation Performance Modeling

作者: Xin Li

作者单位: Department of Electrical & Computer Engineering,Carnegie Mellon University,Pittsburgh,PA 15213 USA

会议类型: 国际会议

会议名称: 2009 IEEE 8th International Conference on ASIC(第八届IEEE国际专用集成电路大会)

会议地点: 长沙

会议语种:英文

页码: 646-649

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）