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ファイル | 記述 | サイズ | フォーマット | |
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transfun.E99.A.1390.pdf | 1.64 MB | Adobe PDF | 見る/開く |
タイトル: | Efficient aging-aware SRAM failure probability calculation via particle filter-based importance sampling |
著者: | Awano, Hiromitsu Hiromoto, Masayuki Sato, Takashi https://orcid.org/0000-0002-1577-8259 (unconfirmed) |
著者名の別形: | 粟野, 皓光 廣本, 正之 佐藤, 高史 |
キーワード: | SRAM cell yield failure probability calculation NBTI importance sampling particle filter Monte Carlo method |
発行日: | 1-Jul-2016 |
出版者: | Institute of Electronics, Information and Communication Engineers(IEICE) |
誌名: | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
巻: | E99.A |
開始ページ: | 1390 |
終了ページ: | 1399 |
抄録: | 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. |
著作権等: | © 2016 The Institute of Electronics, Information and Communication Engineers. |
URI: | http://hdl.handle.net/2433/217470 |
DOI(出版社版): | 10.1587/transfun.E99.A.1390 |
出現コレクション: | 学術雑誌掲載論文等 |
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