Voltage-Controlled Spintronic Stochastic Neuron for Restricted Boltzmann Machine With Weight Sparsity
Jiefang Deng, Venkata Pavan Kumar Miriyala, Zhifeng Zhu, Xuanyao Fong, Gengchiau Liang
Abstract
This work proposes a novel three-terminal magnetic tunnel junction (MTJ) as a stochastic neuron. The neuron is probabilistically switched based on the voltage-controlled magnetic anisotropy (VCMA) effect with the assistance of Rashba effective field. We find that a restricted Boltzmann machine (RBM) implemented using our proposed neuron for handwritten character recognition can achieve synaptic weight sparsity, without sacrificing the network classification accuracy. Moreover, the RBM implemented by this novel neuron performs even better in the presence of device variations, implying that our device is highly suitable for the hardware implementation of RBM.