| Presentation | 2014/11/19 An efficient calculation of RTN-induced SRAM failure probability Hiromitsu AWANO, Masayuki HIROMOTO, Takashi SATO, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Failure rate degradation of an SRAM cell due to random telegraph noise (RTN) is calculated for the first time. An efficient calculation method of RTN-induced SRAM failure probability has been developed to exhaustively cover a large number of possible bias-voltage combinations on which RTN statistics strongly depend. In order to shorten computational time, the Monte Carlo calculation of a single gate-bias condition is accelerated by incorporating two techniques: 1) construction of an optimal importance sampling using particles that move about the "important" regions in a variability space, and 2) a classifier that quickly judges whether the random samples are in failure regions or not. We show that the proposed method achieves at least 15.6× speed-up over the state-of-the-art method. We then integrate an RTN model to modulate failure probability. In our experiment, RTN worsens failure probability by six times than that calculated without the effect of RTN. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | random telegraph noise / SRAM / failure probability / importance sampling / Monte Carlo method |
| Paper # | VLD2014-74,DC32014-28 |
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| Conference Information | |
| Committee | DC |
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| Conference Date | 2014/11/19(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Dependable Computing (DC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An efficient calculation of RTN-induced SRAM failure probability |
| Sub Title (in English) | |
| Keyword(1) | random telegraph noise |
| Keyword(2) | SRAM |
| Keyword(3) | failure probability |
| Keyword(4) | importance sampling |
| Keyword(5) | Monte Carlo method |
| 1st Author's Name | Hiromitsu AWANO |
| 1st Author's Affiliation | Graduate School of Informatics, Kyoto University() |
| 2nd Author's Name | Masayuki HIROMOTO |
| 2nd Author's Affiliation | Graduate School of Informatics, Kyoto University |
| 3rd Author's Name | Takashi SATO |
| 3rd Author's Affiliation | Graduate School of Informatics, Kyoto University |
| Date | 2014/11/19 |
| Paper # | VLD2014-74,DC32014-28 |
| Volume (vol) | vol.114 |
| Number (no) | 329 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |