Stochastic Process Variation in Deep-Submicron CMOS (eBook)

Amir Zjajo received the M.Sc. and DIC degrees from the Imperial College London, London, U.K., in 2000 and the Ph.D. degree from Eindhoven University of Technology, Eindhoven, The Netherlands in 2010, all in electrical engineering. In 2000, he joined Philips Research Laboratories as a member of the research staff in the Mixed-Signal Circuits and Systems Group. From 2006 until 2009, he was with Corporate Research of NXP Semiconductors as a senior research scientist. In 2009, he joined Delft University of Technology as a Faculty member in the Circuit and Systems Group.Dr. Zjajo has published more than 70 papers in referenced journals and conference proceedings, and holds more than 10 US patents or patents pending. He is the author of the book Low-Voltage High-Resolution A/D Converters: Design, Test and Calibration (Springer, 2011, Chinese translation, 2012). He serves as a member of Technical Program Committee of IEEE Design, Automation and Test in Europe Conference, IEEE International Symposium on Circuits and Systems and IEEE International Mixed-Signal Circuits, Sensors and Systems Workshop. His research interests include mixed-signal circuit design, signal integrity and timing and yield optimization.

1 Introduction. 1.1 Stochastic Process Variations in Deep-Submicron CMOS. 1.2 Remarks on Current Design Practice. 1.3Motivation. 1.4 Organization of the Book.2. Random Process Variation in Deep-Submicron CMOS. 2.1 Modeling Process Variability. 2.2 Stochastic MNA for Process Variability Analysis. 2.3 Statistical Timing Analysis. 2.4 Yield Constrained Energy Optimization. 2.5 Experimental Results. 2.6 Conclusions.3 Electronic Noise in Deep-Submicron CMOS. 3.1 Stochastic MNA for Noise Analysis. 3.2 Accuracy Considerations. 3.3 Adaptive Numerical Integration Methods. 3.4 Estimation of the Noise Content Contribution. 3.5 Experimental Results. 3.6 Conclusions.4 Thermal Effects in Deep-Submicron CMOS.4.1 Thermal Model. 4.2 Temperature Estimation. 4.3 Reducing Computation Complexity. 4.4 System Level Methodology for Temperature Constrained Power Management. 4.5 Experimental Results. 4.6 Conclusions.5 Circuit Solutions.5.1 Architecture of the System. 5.2 Circuits for Active Monitoring of Temperature and Process Variations. 5.3 Characterization of Process Variability Conditions. 5.4 Experimental Results. 5.5 Conclusions.   6 Conclusions and Recommendations. 6.1 Summary of the Results. 6.2 Recommendations and Future Research. Appendix. References. Acknowledgement. About the Author.