Spin-Based Neuron Model with Domain Wall Magnets as Synapse
  We present artificial neural network design using spin devices that achieves ultra low voltage operation, low power consumption, high speed, and high integration density. We employ spin torque switched nano-magnets for modelling neuron and domain wall magnets for compact, programmable synapses. The spin based neuron-synapse units operate locally at ultra low supply voltage of 30mV resulting in low computation power. CMOS based inter-neuron 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 shows 95% lower power consumption as compared to 45nm CMOS design. 
Mrigank Sharad, Charles Augustine, Georgios Panagopoulos and Kaushik   Roy
cond-mat.dis-nn cond-mat.mes-hall physics.comp-ph