Multilayer Magnetic Domain Wall MTJ-based Spiking Neural Network

Spintronic devices, especially the magnetic tunnel junction and magnetic domain wall-based devices, hold significant promise for applications in energy-efficient data storage and Unconventional computing architectures. We present a novel multilayer spintronic neuromorphic device based on spin-orbit torque-driven domain wall dynamics. The typical leaky integrate and fire LIF neuron-like characteristics are realized using the combination of SOT and demagnetization energy effects. The device characteristics are modelled as the modified LIF model. We test the spiking neuron model for the classification of the MNIST dataset by emulating a 3-layer spiking neural network SNN -based on the DW-MTJ LIF neuron model. The network achieves classification accuracy above 96% thus the proposed device can be integrated with the CMOS for energy efficient neuromorphic computing.