Spin-Based Neuron Model With Domain-Wall Magnets as Synapse

We present artificial neural network design using spin devices that achieves ultralow voltage operation, low power consumption, high speed, and high integration density. We employ spin torque switched nanomagnets for modeling neuron and domain-wall magnets for compact, programmable synapses. The spin-based neuron-synapse units operate locally at ultralow supply voltage of 30 mV resulting in low computation power. CMOS-based interneuron communication is employed to realize network-level functionality. We corroborate circuit operation with physics-based models developed for the spin devices. Simulation results for character recognition as a benchmark application show 95% lower power consumption as compared to 45-nm CMOS design.