Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning

Y. Ohsawa; H. Yoda; N. Shimomura; S. Shirotori; S. Fujita; K. Koi; B. Altansargai; S. Oikawa; M. Shimizu; Y. Kato; T. Inokuchi; H. Sugiyama; M. Ishikawa; T. Ajay; K. Ikegami; S. Takaya; A. Kurobe

doi:10.1109/EDTM.2018.8421494

Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning

Y. Ohsawa, H. Yoda, N. Shimomura, S. Shirotori, S. Fujita, K. Koi, B. Altansargai, S. Oikawa, M. Shimizu, Y. Kato, T. Inokuchi, H. Sugiyama, M. Ishikawa, T. Ajay, K. Ikegami, S. Takaya, A. Kurobe

Toshiba Corporation

研究成果: 書籍の章/レポート/Proceedings › 会議への寄与 › 査読

3 被引用数 (Scopus)

抄録

Our new proposal of voltage-control spintronics memory (VoCSM) in which spin-orbit torque (SOT) in conjunction with the voltage-control-magnetic-anisotropy (VCMA) effect works as the writing principle showed small switching current of 37 μ A for about 350 KBT switching energy. This indicates VoCSM's writing efficiency is so high that VoCSM would be applicable for deep learning (DL) memories requiring ultra-low energy consumption.

本文言語	英語
ホスト出版物のタイトル	2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	214-216
ページ数	3
ISBN（印刷版）	9781538637111
DOI	https://doi.org/10.1109/EDTM.2018.8421494
出版ステータス	出版済み - 26 7月 2018
外部発表	はい
イベント	2nd IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Kobe, 日本継続期間: 13 3月 2018 → 16 3月 2018

出版物シリーズ

名前	2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings

会議

会議	2nd IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018
国/地域	日本
City	Kobe
Period	13/03/18 → 16/03/18

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

文献へのアクセス

10.1109/EDTM.2018.8421494

他のファイルとリンク

Scopusの出版物のリンク

フィンガープリント

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引用スタイル

Ohsawa, Y., Yoda, H., Shimomura, N., Shirotori, S., Fujita, S., Koi, K., Altansargai, B., Oikawa, S., Shimizu, M., Kato, Y., Inokuchi, T., Sugiyama, H., Ishikawa, M., Ajay, T., Ikegami, K., Takaya, S., & Kurobe, A. (2018). Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning. In 2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings (pp. 214-216). 記事 8421494 (2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EDTM.2018.8421494

Ohsawa, Y. ; Yoda, H. ; Shimomura, N. その他. / Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning. 2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 214-216 (2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings).

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abstract = "Our new proposal of voltage-control spintronics memory (VoCSM) in which spin-orbit torque (SOT) in conjunction with the voltage-control-magnetic-anisotropy (VCMA) effect works as the writing principle showed small switching current of 37 μ A for about 350 KBT switching energy. This indicates VoCSM's writing efficiency is so high that VoCSM would be applicable for deep learning (DL) memories requiring ultra-low energy consumption.",

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author = "Y. Ohsawa and H. Yoda and N. Shimomura and S. Shirotori and S. Fujita and K. Koi and B. Altansargai and S. Oikawa and M. Shimizu and Y. Kato and T. Inokuchi and H. Sugiyama and M. Ishikawa and T. Ajay and K. Ikegami and S. Takaya and A. Kurobe",

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Ohsawa, Y, Yoda, H, Shimomura, N, Shirotori, S, Fujita, S, Koi, K, Altansargai, B, Oikawa, S, Shimizu, M, Kato, Y, Inokuchi, T, Sugiyama, H, Ishikawa, M, Ajay, T, Ikegami, K, Takaya, S & Kurobe, A 2018, Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning. in 2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings., 8421494, 2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 214-216, 2nd IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018, Kobe, 日本, 13/03/18. https://doi.org/10.1109/EDTM.2018.8421494

Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning. / Ohsawa, Y.; Yoda, H.; Shimomura, N. その他.
2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 214-216 8421494 (2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings).

研究成果: 書籍の章/レポート/Proceedings › 会議への寄与 › 査読

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AU - Shirotori, S.

AU - Fujita, S.

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AU - Oikawa, S.

AU - Shimizu, M.

AU - Kato, Y.

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AU - Sugiyama, H.

AU - Ishikawa, M.

AU - Ajay, T.

AU - Ikegami, K.

AU - Takaya, S.

AU - Kurobe, A.

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Ohsawa Y, Yoda H, Shimomura N, Shirotori S, Fujita S, Koi K その他. Ultra-high-efficient Writing in Voltage-Control Spintronics Memory(VoCSM); The Most Promising Embedded Memory for Deep Learning. In 2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 214-216. 8421494. (2018 IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2018 - Proceedings). doi: 10.1109/EDTM.2018.8421494