Spintronic devices for neuromorphic computing

Human brains can solve many problems with orders of magnitude more energy efficiency than traditional computers. As the importance of such problems, like image, voice, and video recognition increases, so does the drive to develop computers that approach the energy efficiency of the brain. Progress must come on many fronts ranging from new algorithms to novel devices that are optimized to function in ways more suited to these algorithms than the digital transistors that have been optimized for the present approaches to computing. Magnetic tunnel junctions have several properties that make them attractive for such applications. They are actively being developed for integration into CMOS integrated circuits to provide non-volatile memory. This development makes it feasible to consider other geometries that have different properties. By changing the shape of the devices, they can be non-volatile binary devices, thermally unstable superparamagnetic binary devices, and non-linear oscillators. In this talk, I describe a few of the computing primitives that have been constructed based on the different functionalities of magnetic tunnel junctions. After a brief overview of other approaches, I will focus on two that I have been involved in. The first of these uses tunnel junctions as non-linear oscillators in the first nanoscale “reservoir” for reservoir computing. The second uses them in their superparamagnetic state as the basis for a population coding scheme. I will discuss the prospects for these primitives to be the basis for energy efficient computing schemes.