  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-switching operation of
magneto-metallic spin torque devices can potentially be more suitable for
non-Boolean computation schemes that can exploit current-mode analog
processing. Device circuit co-design for different classes of
non-Boolean-architectures using spin-torque based neuron models in spin-CMOS
hybrid circuits show that the spin-based non-Boolean 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.
