Downloads: 132

Files in This Item:
File Description SizeFormat 
transfun.E99.A.1390.pdf1.64 MBAdobe PDFView/Open
Title: Efficient aging-aware SRAM failure probability calculation via particle filter-based importance sampling
Authors: Awano, Hiromitsu  kyouindb  KAKEN_id
Hiromoto, Masayuki  kyouindb  KAKEN_id
Sato, Takashi  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-1577-8259 (unconfirmed)
Author's alias: 粟野, 皓光
廣本, 正之
佐藤, 高史
Keywords: SRAM cell yield
failure probability calculation
NBTI
importance sampling
particle filter
Monte Carlo method
Issue Date: 1-Jul-2016
Publisher: Institute of Electronics, Information and Communication Engineers(IEICE)
Journal title: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume: E99.A
Start page: 1390
End page: 1399
Abstract: An efficient Monte Carlo (MC) method for the calculation of failure probability degradation of an SRAM cell due to negative bias temperature instability (NBTI) is proposed. In the proposed method, a particle filter is utilized to incrementally track temporal performance changes in an SRAM cell. The number of simulations required to obtain stable particle distribution is greatly reduced, by reusing the final distribution of the particles in the last time step as the initial distribution. Combining with the use of a binary classifier, with which an MC sample is quickly judged whether it causes a malfunction of the cell or not, the total number of simulations to capture the temporal change of failure probability is significantly reduced. The proposed method achieves 13:4× speed-up over the state-ofthe-art method.
Rights: © 2016 The Institute of Electronics, Information and Communication Engineers.
URI: http://hdl.handle.net/2433/217470
DOI(Published Version): 10.1587/transfun.E99.A.1390
Appears in Collections:Journal Articles

Show full item record

Export to RefWorks


Export Format: 


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.