Physics matters: Statistical aging prediction under trapping/detrapping

Jyothi Bhaskarr Velamala, Ketul Sutaria, Takashi Sato, Yu Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Citations (Scopus)

Abstract

Randomness in Negative Bias Temperature Instability (NBTI) process poses a dramatic challenge on reliability prediction of digital circuits. Accurate statistical aging prediction is essential in order to develop robust guard banding and protection strategies during the design stage. Variations in device level and supply voltage due to Dynamic Voltage Scaling (DVS) need to be considered in aging analysis. The statistical device data collected from 65nm test chip shows that degradation behavior derived from trapping/detrapping mechanism is accurate under statistical variations compared to conventional Reaction Diffusion (RD) theory. The unique features of this work include (1) Aging model development as a function of technology parameters based on trapping/detrapping theory (2) Reliability prediction under device variations and DVS with solid validation with using 65nm statistical silicon data (3) Asymmetric aged timing analysis under NBTI and comprehensive evaluation of our framework in ISCAS89 sequential circuits. Further, we show that RD based NBTI model significantly overestimates the degradation and TD model correctly captures aging variability. These results provide design insights under statistical NBTI aging and enhance the prediction efficiency.

Original languageEnglish (US)
Title of host publicationProceedings - Design Automation Conference
Pages139-144
Number of pages6
DOIs
StatePublished - 2012
Event49th Annual Design Automation Conference, DAC '12 - San Francisco, CA, United States
Duration: Jun 3 2012Jun 7 2012

Other

Other49th Annual Design Automation Conference, DAC '12
CountryUnited States
CitySan Francisco, CA
Period6/3/126/7/12

Fingerprint

Trapping
Physics
Aging of materials
Prediction
Dynamic Voltage Scaling
Reaction-diffusion
Degradation
Timing Analysis
Sequential circuits
Comprehensive Evaluation
Digital Circuits
Digital circuits
Randomness
Silicon
Chip
Voltage
Model
Negative bias temperature instability
Electric potential
Design

Keywords

  • dynamic voltage scaling
  • hole trapping
  • negative bias temperature instability
  • timing violations

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

Cite this

Velamala, J. B., Sutaria, K., Sato, T., & Cao, Y. (2012). Physics matters: Statistical aging prediction under trapping/detrapping. In Proceedings - Design Automation Conference (pp. 139-144) https://doi.org/10.1145/2228360.2228388

Physics matters : Statistical aging prediction under trapping/detrapping. / Velamala, Jyothi Bhaskarr; Sutaria, Ketul; Sato, Takashi; Cao, Yu.

Proceedings - Design Automation Conference. 2012. p. 139-144.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Velamala, JB, Sutaria, K, Sato, T & Cao, Y 2012, Physics matters: Statistical aging prediction under trapping/detrapping. in Proceedings - Design Automation Conference. pp. 139-144, 49th Annual Design Automation Conference, DAC '12, San Francisco, CA, United States, 6/3/12. https://doi.org/10.1145/2228360.2228388
Velamala JB, Sutaria K, Sato T, Cao Y. Physics matters: Statistical aging prediction under trapping/detrapping. In Proceedings - Design Automation Conference. 2012. p. 139-144 https://doi.org/10.1145/2228360.2228388
Velamala, Jyothi Bhaskarr ; Sutaria, Ketul ; Sato, Takashi ; Cao, Yu. / Physics matters : Statistical aging prediction under trapping/detrapping. Proceedings - Design Automation Conference. 2012. pp. 139-144
@inproceedings{225ad4815c6c47b78f23484d3ca2ba14,
title = "Physics matters: Statistical aging prediction under trapping/detrapping",
abstract = "Randomness in Negative Bias Temperature Instability (NBTI) process poses a dramatic challenge on reliability prediction of digital circuits. Accurate statistical aging prediction is essential in order to develop robust guard banding and protection strategies during the design stage. Variations in device level and supply voltage due to Dynamic Voltage Scaling (DVS) need to be considered in aging analysis. The statistical device data collected from 65nm test chip shows that degradation behavior derived from trapping/detrapping mechanism is accurate under statistical variations compared to conventional Reaction Diffusion (RD) theory. The unique features of this work include (1) Aging model development as a function of technology parameters based on trapping/detrapping theory (2) Reliability prediction under device variations and DVS with solid validation with using 65nm statistical silicon data (3) Asymmetric aged timing analysis under NBTI and comprehensive evaluation of our framework in ISCAS89 sequential circuits. Further, we show that RD based NBTI model significantly overestimates the degradation and TD model correctly captures aging variability. These results provide design insights under statistical NBTI aging and enhance the prediction efficiency.",
keywords = "dynamic voltage scaling, hole trapping, negative bias temperature instability, timing violations",
author = "Velamala, {Jyothi Bhaskarr} and Ketul Sutaria and Takashi Sato and Yu Cao",
year = "2012",
doi = "10.1145/2228360.2228388",
language = "English (US)",
isbn = "9781450311991",
pages = "139--144",
booktitle = "Proceedings - Design Automation Conference",

}

TY - GEN

T1 - Physics matters

T2 - Statistical aging prediction under trapping/detrapping

AU - Velamala, Jyothi Bhaskarr

AU - Sutaria, Ketul

AU - Sato, Takashi

AU - Cao, Yu

PY - 2012

Y1 - 2012

N2 - Randomness in Negative Bias Temperature Instability (NBTI) process poses a dramatic challenge on reliability prediction of digital circuits. Accurate statistical aging prediction is essential in order to develop robust guard banding and protection strategies during the design stage. Variations in device level and supply voltage due to Dynamic Voltage Scaling (DVS) need to be considered in aging analysis. The statistical device data collected from 65nm test chip shows that degradation behavior derived from trapping/detrapping mechanism is accurate under statistical variations compared to conventional Reaction Diffusion (RD) theory. The unique features of this work include (1) Aging model development as a function of technology parameters based on trapping/detrapping theory (2) Reliability prediction under device variations and DVS with solid validation with using 65nm statistical silicon data (3) Asymmetric aged timing analysis under NBTI and comprehensive evaluation of our framework in ISCAS89 sequential circuits. Further, we show that RD based NBTI model significantly overestimates the degradation and TD model correctly captures aging variability. These results provide design insights under statistical NBTI aging and enhance the prediction efficiency.

AB - Randomness in Negative Bias Temperature Instability (NBTI) process poses a dramatic challenge on reliability prediction of digital circuits. Accurate statistical aging prediction is essential in order to develop robust guard banding and protection strategies during the design stage. Variations in device level and supply voltage due to Dynamic Voltage Scaling (DVS) need to be considered in aging analysis. The statistical device data collected from 65nm test chip shows that degradation behavior derived from trapping/detrapping mechanism is accurate under statistical variations compared to conventional Reaction Diffusion (RD) theory. The unique features of this work include (1) Aging model development as a function of technology parameters based on trapping/detrapping theory (2) Reliability prediction under device variations and DVS with solid validation with using 65nm statistical silicon data (3) Asymmetric aged timing analysis under NBTI and comprehensive evaluation of our framework in ISCAS89 sequential circuits. Further, we show that RD based NBTI model significantly overestimates the degradation and TD model correctly captures aging variability. These results provide design insights under statistical NBTI aging and enhance the prediction efficiency.

KW - dynamic voltage scaling

KW - hole trapping

KW - negative bias temperature instability

KW - timing violations

UR - http://www.scopus.com/inward/record.url?scp=84863538466&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84863538466&partnerID=8YFLogxK

U2 - 10.1145/2228360.2228388

DO - 10.1145/2228360.2228388

M3 - Conference contribution

AN - SCOPUS:84863538466

SN - 9781450311991

SP - 139

EP - 144

BT - Proceedings - Design Automation Conference

ER -