论文标题
由四端MTJ设备启用了无CMOS多层感知器
CMOS-Free Multilayer Perceptron Enabled by Four-Terminal MTJ Device
论文作者
论文摘要
神经形态计算有望在处理非结构化信息的应用程序中对常规系统的革命性改进。为了充分意识到这一潜力，神经形态系统应利用新兴纳米版本的仿生行为。特别是，SpinTronic设备的非挥发性和模拟功能提供了出色的机会。虽然先前已经提出了旋转器装置来模仿神经元和突触，但需要互补的金属氧化物 - 氧化型（CMOS）设备来实现多层旋转式perceptron横梁。因此，这项工作提出了一种新的旋转神经元，该神经元纯粹可以纯粹的自旋多层多层感知，从而消除了对CMOS电路的需求并简化了制造。
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 have previously been proposed that emulate neurons and synapses, complementary metal-oxide-semiconductor (CMOS) devices are required to implement multilayer spintronic perceptron crossbars. This work therefore proposes a new spintronic neuron that enables purely spintronic multilayer perceptrons, eliminating the need for CMOS circuitry and simplifying fabrication.
