@article{b7c848a8efc246efbe0cb745a57fc382,
title = "Ultra-high-efficiency writing in voltage-control spintronics memory (VoCSM): The most promising embedded memory for deep learning",
abstract = "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 μA for about 350 KBT 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.",
keywords = "learning (artificial intelligence), magnetic devices, Magnetic memory, magnetic tunneling, Nanopatterning, nonvolatile memory",
author = "Y. Ohsawa and H. Yoda and N. Shimomura and S. Shirotori and S. Fujita and K. Koi and A. Buyandalai and S. Oikawa and M. Shimizu and Y. Kato and T. Inokuchi and H. Sugiyama and M. Ishikawa and K. Ikegami and S. Takaya and A. Kurobe",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",
year = "2018",
doi = "10.1109/JEDS.2018.2880752",
language = "English",
volume = "6",
pages = "1238--1243",
journal = "IEEE Journal of the Electron Devices Society",
issn = "2168-6734",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
}