Purely Spintronic Leaky Integrate-and-Fire Neurons

被引：4

作者：

Brigner, Wesley H. ^{[1
]}

Hassan, Naimul ^{[1
]}

Hu, Xuan ^{[1
]}

Bennett, Christopher H. ^{[2
]}

Garcia-Sanchez, Felipe ^{[3
,4
]}

Marinella, Matthew J. ^{[6
]}

Incorvia, Jean Anne C. ^{[5
]}

Friedman, Joseph S. ^{[1
]}

机构：

[1] Univ Texas Dallas, Elect & Comp Engn, Richardson, TX 75080 USA

[2] Sandia Natl Labs, Albuquerque, NM 87185 USA

[3] Ist Nazl Ric Metrol, Turin, Italy

[4] Univ Salamanca, Dept Appl Phys, Salamanca 37008, Spain

[5] Univ Texas Austin, Elect & Comp Engn, Austin, TX 78705 USA

[6] Arizona State Univ, Elect & Comp Engn, Tempe, AZ 85287 USA

来源：

2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22) | 2022年

关键词：

Artificial neural network; Neuromorphic computing; Leaky integrate-and-fire neuron; NETWORK;

D O I：

10.1109/ISCAS48785.2022.9937890

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information. To fully realize this potential, neuromorphic systems should exploit the biomimetic behavior of emerging nanodevices. In particular, exceptional opportunities are provided by the non-volatility and analog capabilities of spintronic devices. While spintronic devices that emulate neurons have been previously proposed, they require complementary metal-oxide semiconductor (CMOS) technology to function. In turn, this significantly increases the power consumption, fabrication complexity, and device area of a single neuron. This work reviews three previously proposed

引用

页码：1189 / 1193

页数：5

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