Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron

被引:33
作者
Brigner, Wesley H. [1 ]
Hu, Xuan [1 ]
Hassan, Naimul [1 ]
Bennett, Christopher H. [2 ]
Incorvia, Jean Anne C. [3 ]
Garcia-Sanchez, Felipe [4 ,5 ]
Friedman, Joseph S. [1 ]
机构
[1] Univ Texas Dallas, Dept Elect & Comp Engn, Richardson, TX 75080 USA
[2] Sandia Natl Labs, Albuquerque, NM 87123 USA
[3] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA
[4] Ist Nazl Ric Metrol, I-10135 Turin, Italy
[5] Univ Salamanca, Dept Fis Aplicada, E-37008 Salamanca, Spain
来源
IEEE JOURNAL ON EXPLORATORY SOLID-STATE COMPUTATIONAL DEVICES AND CIRCUITS | 2019年 / 5卷 / 01期
关键词
Artificial neuron; leaky integrate-and-fire (LIF) neuron; magnetic domain wall (DW); neural network crossbar; neuromorphic computing; three-terminal magnetic tunnel junction (3T-MTJ); MOTION; NETWORKS; PROPOSAL;
D O I
10.1109/JXCDC.2019.2904191
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Spintronic three-terminal magnetic-tunnel-junction (3T-MTJ) devices have gained considerable interest in the field of neuromorphic computing. Previously, these devices required external circuitry to implement the leaking functionality that leaky integrate-and-fire (LIF) neurons should display. However, the use of external circuitry results in decreased device efficiency. We previously demonstrated lateral inhibition with a 3T-MTJ neuron that intrinsically performs the leaking, integrating, and firing functions; however, it required the fabrication of a complex multilayer structure. In this paper, we introduce an anisotropy gradient to implement a single-layer intrinsically leaking 3T-MTJ LIF neuron without the use of any external circuitry. This provides the leaking functionality with no hardware cost and reduced fabrication complexity, which increases the device, circuit, system, and cost efficiency.
引用
收藏
页码:19 / 24
页数:6
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