Ultra-High-Efficiency Writing in Voltage-Control Spintronics Memory (VoCSM): The Most Promising Embedded Memory for Deep Learning | Zendy

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

Open Access

Ultra-High-Efficiency Writing in Voltage-Control Spintronics Memory (VoCSM): The Most Promising Embedded Memory for Deep Learning

Author(s) -

Y. Ohsawa,

H. Yoda,

N. Shimomura,

S. Shirotori,

S. Fujita,

K. Koi,

A. Buyandalai,

S. Oikawa,

M. Shimizu,

Y. Kato,

T. Inokuchi,

H. Sugiyama,

M. Ishikawa,

K. Ikegami,

S. Takaya,

A. Kurobe

Publication year - 2018

Publication title -

ieee journal of the electron devices society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.69

H-Index - 31

ISSN - 2168-6734

DOI - 10.1109/jeds.2018.2880752

Subject(s) - components, circuits, devices and systems , engineered materials, dielectrics and plasmas

Our new proposal of voltage-control spintronics memory (VoCSM) in which spin-orbit torque in conjunction with the voltage-control-magnetic-anisotropy effect works as the writing principle showed small switching current of

$37~\mu \text{A}$

for about 350

$K_{B}T$

switching energy. This indicates VoCSM’s writing efficiency is so high that VoCSM would be applicable for deep learning memories requiring ultra-low power consumption.

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