Title :
A study of statistical variability-aware methods
Author :
Hao Cai ; Kaikai Liu ; de Barros Naviner, Lirida Alves
Author_Institution :
LTCI, Telecom-ParisTech, Paris, France
Abstract :
Conventionally circuit performance variability is analyzed with Monte-Carlo simulation and design corner analysis. On the other hand, statistical methods such as design of experiments (DoEs), response surface modeling (RSM) and compact modeling (CM) can achieve a better trade-off between simulation efficiency and accuracy. This paper investigates these variability-aware analysis methodologies. Based on industry standard BSIM4 compact model, selected physical parameters are applied to DoE-RSM and CM methods. Methodologies are validated with both analog (op-amp) and digital circuits (flip-flop) at 65 nm node. A 3X speed up is achieved with DoE-RSM. A proper selection of CM parameters is critical to model accuracy.
Keywords :
analogue circuits; design of experiments; digital circuits; flip-flops; response surface methodology; DoE-RSM; analog circuits; digital circuits; flip-flop; industry standard BSIM4 compact model; size 65 nm; statistical variability-aware methods; Accuracy; Analytical models; Circuit optimization; Correlation; Delays; Integrated circuit modeling; Mathematical model;
Conference_Titel :
Radio-Frequency Integration Technology (RFIT), 2014 IEEE International Symposium on
Conference_Location :
Hefei
DOI :
10.1109/RFIT.2014.6933246
