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.
| Original language | English (US) |
|---|---|
| Title of host publication | 2015 International Joint Conference on Neural Networks, IJCNN 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781479919604, 9781479919604, 9781479919604, 9781479919604 |
| DOIs | |
| State | Published - Sep 28 2015 |
| Event | International Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland Duration: Jul 12 2015 → Jul 17 2015 |
Publication series
| Name | Proceedings of the International Joint Conference on Neural Networks |
|---|---|
| Volume | 2015-September |
Conference
| Conference | International Joint Conference on Neural Networks, IJCNN 2015 |
|---|---|
| Country | Ireland |
| City | Killarney |
| Period | 7/12/15 → 7/17/15 |
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All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
Cite this
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Spin-Transfer Torque Magnetic neuron for low power neuromorphic computing. / Sengupta, Abhronil; Roy, Kaushik.
2015 International Joint Conference on Neural Networks, IJCNN 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7280306 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Spin-Transfer Torque Magnetic neuron for low power neuromorphic computing
AU - Sengupta, Abhronil
AU - Roy, Kaushik
PY - 2015/9/28
Y1 - 2015/9/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84951113578&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84951113578&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2015.7280306
DO - 10.1109/IJCNN.2015.7280306
M3 - Conference contribution
AN - SCOPUS:84951113578
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2015 International Joint Conference on Neural Networks, IJCNN 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -