A study of statistical variability-aware methods

Hao Cai; Kaikai Liu; Lirida Alves De Barros Naviner

doi:10.1109/RFIT.2014.6933246

A study of statistical variability-aware methods

Hao Cai
, Kaikai Liu
, Lirida Alves De Barros Naviner

Institut Mines-Télécom

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology
Subtitle of host publication	Silicon Technology Heats Up for THz
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479955039
DOIs	https://doi.org/10.1109/RFIT.2014.6933246
Publication status	Published - 21 Oct 2014
Externally published	Yes
Event	2014 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2014 - Hefei, China Duration: 27 Aug 2014 → 30 Aug 2014

Publication series

Name	RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz

Conference

Conference	2014 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2014
Country/Territory	China
City	Hefei
Period	27/08/14 → 30/08/14

Access to Document

10.1109/RFIT.2014.6933246

Cite this

Cai, H., Liu, K., & De Barros Naviner, L. A. (2014). A study of statistical variability-aware methods. In RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz Article 6933246 (RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RFIT.2014.6933246

Cai, Hao ; Liu, Kaikai ; De Barros Naviner, Lirida Alves. / A study of statistical variability-aware methods. RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz. Institute of Electrical and Electronics Engineers Inc., 2014. (RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz).

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title = "A study of statistical variability-aware methods",

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.",

author = "Hao Cai and Kaikai Liu and \{De Barros Naviner\}, \{Lirida Alves\}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2014 ; Conference date: 27-08-2014 Through 30-08-2014",

year = "2014",

month = oct,

day = "21",

doi = "10.1109/RFIT.2014.6933246",

language = "English",

series = "RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz",

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Cai, H, Liu, K & De Barros Naviner, LA 2014, A study of statistical variability-aware methods. in RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz., 6933246, RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz, Institute of Electrical and Electronics Engineers Inc., 2014 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2014, Hefei, China, 27/08/14. https://doi.org/10.1109/RFIT.2014.6933246

A study of statistical variability-aware methods. / Cai, Hao; Liu, Kaikai; De Barros Naviner, Lirida Alves.
RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz. Institute of Electrical and Electronics Engineers Inc., 2014. 6933246 (RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A study of statistical variability-aware methods

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AU - Liu, Kaikai

AU - De Barros Naviner, Lirida Alves

PY - 2014/10/21

Y1 - 2014/10/21

N2 - 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.

AB - 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.

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DO - 10.1109/RFIT.2014.6933246

M3 - Conference contribution

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T3 - RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology, RFIT 2014

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Cai H, Liu K, De Barros Naviner LA. A study of statistical variability-aware methods. In RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz. Institute of Electrical and Electronics Engineers Inc. 2014. 6933246. (RFIT 2014 - 2014 IEEE International Symposium on Radio-Frequency Integration Technology: Silicon Technology Heats Up for THz). doi: 10.1109/RFIT.2014.6933246

A study of statistical variability-aware methods

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