@inproceedings{d500472606aa426fbb7b8850c81dfda9,
title = "Spin-Transfer Torque Magnetic neuron for low power neuromorphic computing",
abstract = "Neuromorphic computing attempts to emulate the remarkable efficiency of the human brain in vision, perception and cognition related tasks. Nanoscale devices that offer a direct mapping to the underlying neural computations have emerged as a promising candidate for such neuromorphic architectures. In this paper, a Magnetic Tunneling Junction (MTJ) has been proposed to perform the thresholding operation of a biological neuron. A crossbar array consisting of programmable resistive synapses generates an excitatory / inhibitory charge current input to the neuron. The magnetization of the free layer of the MTJ is manipulated by Spin-Transfer Torque generated by the net synaptic current. Algorithm, device and circuit co-simulation framework suggest the possibility of ∼ 1.63 - 1.79x power savings in comparison to a 45nm digital CMOS implementation.",
author = "Abhronil Sengupta and Kaushik Roy",
year = "2015",
month = sep,
day = "28",
doi = "10.1109/IJCNN.2015.7280306",
language = "English (US)",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 International Joint Conference on Neural Networks, IJCNN 2015",
address = "United States",
note = "International Joint Conference on Neural Networks, IJCNN 2015 ; Conference date: 12-07-2015 Through 17-07-2015",
}