Boolean and non-Boolean computation with spin devices

Recently several device and circuit design techniques have been explored for applying nano-magnets and spin torque devices like spin valves and domain wall magnets in computational hardware. However, most of them have been focused on digital logic, and, their benefits over robust and high performance CMOS remains debatable. Ultra-low voltage, current-mode operation of magneto-metallic spin torque devices can potentially be more suitable for non-Boolean logic like neuromorphic computation, which involve analog processing. Device circuit co-design for different classes of neuromorphic architectures using spin-torque based neuron models along with DWM or other memristive synapses show that the spin-based neuromorphic designs can achieve 15X-100X lower computation energy for applications like, image processing, data-conversion, cognitive-computing, pattern matching and programmable-logic, as compared to state of art CMOS designs.