Shape-Based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
Shape-Based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron
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DOI：
10.1109/ted.2019.2938952
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发表时间：
2019-11-01
影响因子：
3.1
通讯作者：
Garcia-Sanchez, Felipe
中科院分区：
文献类型：
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作者：
Brigner, Wesley H.;Friedman, Joseph S.;Garcia-Sanchez, Felipe
基于畴壁（DW）在铁磁纳米线轨道中运动的自旋电子器件作为神经形态信息处理系统的组件受到了极大关注。先前关于自旋电子人工神经元的方案需要外部刺激来实现泄漏功能，这是泄漏整合激发（LIF）神经元的三个基本功能之一。使用这种外部磁场或电流刺激会导致能量效率降低或制造复杂性增加。在本文中，我们修改了先前展示的三端磁性隧道结神经元的形状，使其在没有任何外部刺激的情况下实现泄漏操作。梯形结构导致基于形状的畴壁漂移，从而在没有硬件成本的情况下内在地提供了泄漏功能。因此，这种LIF神经元有望推动自旋电子神经网络交叉阵列的发展。
Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Previous proposals for spintronic artificial neurons required external stimuli to perform the leaking functionality, one of the three fundamental functions of a leaky integrate-and-fire (LIF) neuron. The use of this external magnetic field or electrical current stimulus results in either a decrease in energy efficiency or an increase in fabrication complexity. In this article, we modify the shape of previously demonstrated three-terminal magnetic tunnel junction neurons to perform the leaking operation without any external stimuli. The trapezoidal structure causes a shape-based DW drift, thus intrinsically providing the leaking functionality with no hardware cost. This LIF neuron, therefore, promises to advance the development of spintronic neural network crossbar arrays.