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Behavioral modeling and simulations of mixed-signal integrated circuits with process variations and physical defects
by Guo, Yu-Yau, Ph.D., University of Rhode Island, 2003, 102 pages; AAT 3115630

Abstract (Summary)

During fabrication process, mixed analog and digital integrated circuits (ICs) are more susceptible to process variations and physical defects than pure digital ICs. Therefore, it is beneficial to simulate the effects of process variations and defects on mixed-signal designs even before the design goes into production. Simulations of ICs having process variations are performed with Monte Carlo simulations. And, simulations of ICs having physical defects are called fault simulations. However, both simulation schemes require large numbers of instances. Consequently, simulation times can be extremely long, e.g. hours or days. In this System-on-a-Chip (SoC) era, mixed-signal designs are becoming more complex and thus impossible for traditional simulation schemes to be effectively applied.

To dramatically reduce Monte Carlo simulation time and fault simulation time, a new behavioral simulation approach is proposed in this dissertation. Essentially, timing consuming detailed circuit simulations can be replaced by simple linear equations. A flash analog-to-digital converter (ADC) is used here to demonstrate the feasibility of proposed approach. The behavioral models for the flash ADC having process variations and physical defects are built. With these behavioral models, behavioral simulation programs are written in C++ to perform fast Monte Carlo simulations and fault simulations. For the small 3-bit flash ADC, the proposed method reduced the Monte Carlo simulation time, with 30 instances, from 180 hours to a mere 15 minutes. Such dramatic reduction in simulation time was achieved with a maximum prediction error of no more than 6%.

Indexing (document details)

Advisor:Lo, Jien-Chung
School:University of Rhode Island
School Location:United States -- Rhode Island
Keyword(s):Mixed-signal, Integrated circuits, Process variations, Defects
Source:DAI-B 64/12, p. 6237, Jun 2004
Source type:Dissertation
Subjects:Electrical engineering
Publication Number: AAT 3115630
Document URL:http://proquest.umi.com/pqdlink?did=765220401&Fmt=7&clientId =79356&RQT=309&VName=PQD
ProQuest document ID:765220401


 

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