TY - GEN
T1 - Use of analog spintronics device in performing neuro-morphic computing functions
AU - Fukami, Shunsuke
AU - Borders, William A.
AU - Kurenkov, Aleksandr
AU - Zhang, Chaoliang
AU - DuttaGupta, Samik
AU - Ohno, Hideo
N1 - Funding Information:
Acknowledgments: We are grateful for Prof. Hisanao Akima, Prof. Shigeo Sato, and Prof. Yoshihiko Horio for their technical supports and fruitful discussion. A portion of this work was supported by the R&D Project for ICT Key Technology of MEXT, ImPACT Program of CSTI, JST-OPERA, and JSPS KAKENHI 17H06093.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - Since spintronics devices are capable of retaining digital information as -Their magnetization direction, development of nonvolatile memories, so-called magnetoresistive random access memories (MRAMs), to realize low-power integrated circuits with -The von Neumann architecture has been one of -The mainstream outlets of spintronics research pursued in -The last several decades. Meanwhile, neuromorphic-computing hardware with non-von Neumann architecture has started to attract a great deal of attention in -The field of microelectronics. Neuromorphic computing allows for completion of complex tasks at high speeds and at low power consumption levels that conventional von Neumann computers struggle with [1,2]. Recent researches point out that -The spintronics devices also have -The capable characteristics to model -The human brain [3-5]. In this presentation, we describe a proof-of-concept demonstration of an associative memory operation like -The human brain using a spintronics device [6]. For this purpose, we employ a recently-found spin-orbit torque (SOT) induced switching [7-9] device consisting of an antiferromagnet (AFM)/ ferromagnet (FM) stack structure [10-12], which shows an analogue-like resistance switching and thus serves as an artificial synapse in artificial neural networks.
AB - Since spintronics devices are capable of retaining digital information as -Their magnetization direction, development of nonvolatile memories, so-called magnetoresistive random access memories (MRAMs), to realize low-power integrated circuits with -The von Neumann architecture has been one of -The mainstream outlets of spintronics research pursued in -The last several decades. Meanwhile, neuromorphic-computing hardware with non-von Neumann architecture has started to attract a great deal of attention in -The field of microelectronics. Neuromorphic computing allows for completion of complex tasks at high speeds and at low power consumption levels that conventional von Neumann computers struggle with [1,2]. Recent researches point out that -The spintronics devices also have -The capable characteristics to model -The human brain [3-5]. In this presentation, we describe a proof-of-concept demonstration of an associative memory operation like -The human brain using a spintronics device [6]. For this purpose, we employ a recently-found spin-orbit torque (SOT) induced switching [7-9] device consisting of an antiferromagnet (AFM)/ ferromagnet (FM) stack structure [10-12], which shows an analogue-like resistance switching and thus serves as an artificial synapse in artificial neural networks.
UR - http://www.scopus.com/inward/record.url?scp=85045970128&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045970128&partnerID=8YFLogxK
U2 - 10.1109/E3S.2017.8246168
DO - 10.1109/E3S.2017.8246168
M3 - Conference contribution
AN - SCOPUS:85045970128
T3 - 2017 5th Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2017 - Proceedings
SP - 1
EP - 3
BT - 2017 5th Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2017
Y2 - 19 October 2017 through 20 October 2017
ER -