r. Tan received a new three–year grant from National Science Foundation for exploring new techniques for statistical analysis of nanometer analog and mixed-signal circuits. The NSF project is titled SHF:Small:Variational and Bound Performance Analysis of Nanometer Mixed-Signal/Analog Circuits  with 275K for three years (CCF-1116882). Dr. Tan is the single PI for this award.

In this project, Prof. TanÕs team will investigate novel and efficient non-Monte-Carlo techniques for worst-case and statistical analysis of analog/mixed-signal circuits. First, the team will develop novel worst-case analysis methods for analog/mixed-signal circuits based on graph-based symbolic analysis technique, affine-like interval arithmetic and a control-theoretic method. The team will investigate the performance bounds in the time domains given frequency domain bounds. Second, Dr. TanÕs team plans to develop fast non-Monte-Carlo stochastic analysis methods to calculate statistical responses such as mismatch due to process variations. We model the problem as solving nonlinear stochastic differential-algebra-equations. Nonlinear stochastic methods and new nonlinear macromodeling method will be investigated to solve the resulting problems.

Prof. TanÕs team will work with the industry partner IBM Corporation to bring immediate impacts on the design community to improve the design productivity for nanometer VLSI systems.