Multiple sensitive volume based soft error rate estimation with machine learning

Soichi Hirokawa, Ryo Harada, Kenshiro Sakuta, Yukinobu Watanabe, Masanori Hashimoto

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

8 引用 (Scopus)

抜粋

We propose a new methodology for soft error rate estimation using multiple sensitive volumes and machine learning. The proposed methodology assigns multiple sensitive volumes to a unit circuit (e.g. SRAM cell) and constructs a discriminator from TCAD simulations by machine learning. For each ion reproduced by radiation transport simulation, the discriminator judges whether an upset occurs or not, and consequently we can obtain soft error rate by counting the number of events judged as upset events. Advantages of the proposed methodology are: (1) empirical construction and adjustment of sensitive volume and critical charge is no longer necessary, (2) multiple transistors can be easily considered, and (3) event-wise accuracy can be improved. We confirmed the correlation between irradiation results and simulation results for 65-nm silicon on thin buried oxide (SOTB) SRAM. The estimation error was 7% without any empirical optimization of sensitive volume and critical charge.

元の言語英語
ホスト出版物のタイトル2016 16th European Conference on Radiation and Its Effects on Components and Systems, RADECS 2016
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1-4
ページ数4
ISBN(電子版)9781509043668
DOI
出版物ステータス出版済み - 10 31 2017
イベント16th European Conference on Radiation and Its Effects on Components and Systems, RADECS 2016 - Bremen, ドイツ
継続期間: 9 19 20169 23 2016

出版物シリーズ

名前Proceedings of the European Conference on Radiation and its Effects on Components and Systems, RADECS
2016-September

その他

その他16th European Conference on Radiation and Its Effects on Components and Systems, RADECS 2016
ドイツ
Bremen
期間9/19/169/23/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Radiation

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  • これを引用

    Hirokawa, S., Harada, R., Sakuta, K., Watanabe, Y., & Hashimoto, M. (2017). Multiple sensitive volume based soft error rate estimation with machine learning. : 2016 16th European Conference on Radiation and Its Effects on Components and Systems, RADECS 2016 (pp. 1-4). (Proceedings of the European Conference on Radiation and its Effects on Components and Systems, RADECS; 巻数 2016-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RADECS.2016.8093181