IEICE TRANSACTIONS on Fundamentals
Efficient Aging-Aware Failure Probability Estimation Using Augmented Reliability and Subset Simulation
Summary :
A circuit-aging simulation that efficiently calculates temporal change of rare circuit-failure probability is proposed. While conventional methods required a long computational time due to the necessity of conducting separate calculations of failure probability at each device age, the proposed Monte Carlo based method requires to run only a single set of simulation. By applying the augmented reliability and subset simulation framework, the change of failure probability along the lifetime of the device can be evaluated through the analysis of the Monte Carlo samples. Combined with the two-step sample generation technique, the proposed method reduces the computational time to about 1/6 of that of the conventional method while maintaining a sufficient estimation accuracy.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.12 pp.2807-2815
- Publication Date
- 2017/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E100.A.2807
- Type of Manuscript
- Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
- Category
Authors
Hiromitsu AWANO
The University of Tokyo
Takashi SATO
Kyoto University
Keyword
Latest Issue
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Hiromitsu AWANO, Takashi SATO, "Efficient Aging-Aware Failure Probability Estimation Using Augmented Reliability and Subset Simulation" in IEICE TRANSACTIONS on Fundamentals,
vol. E100-A, no. 12, pp. 2807-2815, December 2017, doi: 10.1587/transfun.E100.A.2807.
Abstract: A circuit-aging simulation that efficiently calculates temporal change of rare circuit-failure probability is proposed. While conventional methods required a long computational time due to the necessity of conducting separate calculations of failure probability at each device age, the proposed Monte Carlo based method requires to run only a single set of simulation. By applying the augmented reliability and subset simulation framework, the change of failure probability along the lifetime of the device can be evaluated through the analysis of the Monte Carlo samples. Combined with the two-step sample generation technique, the proposed method reduces the computational time to about 1/6 of that of the conventional method while maintaining a sufficient estimation accuracy.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2807/_p
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@ARTICLE{e100-a_12_2807,
author={Hiromitsu AWANO, Takashi SATO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Efficient Aging-Aware Failure Probability Estimation Using Augmented Reliability and Subset Simulation},
year={2017},
volume={E100-A},
number={12},
pages={2807-2815},
abstract={A circuit-aging simulation that efficiently calculates temporal change of rare circuit-failure probability is proposed. While conventional methods required a long computational time due to the necessity of conducting separate calculations of failure probability at each device age, the proposed Monte Carlo based method requires to run only a single set of simulation. By applying the augmented reliability and subset simulation framework, the change of failure probability along the lifetime of the device can be evaluated through the analysis of the Monte Carlo samples. Combined with the two-step sample generation technique, the proposed method reduces the computational time to about 1/6 of that of the conventional method while maintaining a sufficient estimation accuracy.},
keywords={},
doi={10.1587/transfun.E100.A.2807},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - Efficient Aging-Aware Failure Probability Estimation Using Augmented Reliability and Subset Simulation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2807
EP - 2815
AU - Hiromitsu AWANO
AU - Takashi SATO
PY - 2017
DO - 10.1587/transfun.E100.A.2807
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2017
AB - A circuit-aging simulation that efficiently calculates temporal change of rare circuit-failure probability is proposed. While conventional methods required a long computational time due to the necessity of conducting separate calculations of failure probability at each device age, the proposed Monte Carlo based method requires to run only a single set of simulation. By applying the augmented reliability and subset simulation framework, the change of failure probability along the lifetime of the device can be evaluated through the analysis of the Monte Carlo samples. Combined with the two-step sample generation technique, the proposed method reduces the computational time to about 1/6 of that of the conventional method while maintaining a sufficient estimation accuracy.
ER -
English
