There are many pressing problems today where data-intensive tasks are needed to be accomplished in real time. This can range from sequencing DNA, to self-driving cars recognizing a person walking by, to predicting the trajectory of a flying object. In these examples, traditional computing faces a performance wall where the computing time and energy is severely limited by memory access. If computers could be built closer to the way the brain computes, where memory and computation are densely connected together like the neurons (and synapses) of the brain, these tasks could be performed with a million times less energy. This requires doing research on designing and building artificial neurons and synapses, and research on connecting them together into neuromorphic circuits. Due to the many different kinds of problems this new type of computing will address, research in this area will have impact not only in the semiconductor industry, but also far-reaching impact in medicine, defense, and new technologies. This project will educate and train multiple Ph.D.-level and undergraduate students in this interdisciplinary field, with skills highly sought after in academia, national labs, and industry. It will also have significance for broadening participation of women and under-represented minorities in computing: the researchers seek to educate and train women and Hispanic students from their state of Texas.

Nanodevices made from magnetic materials (such as iron) have many properties that make them uniquely suitable as artificial neurons and synapses to enable such computing. Nevertheless, a number of technical problems remain in using magnetic devices for neuromorphic computing, which this project aims to address: there has been little experimental study of circuits that combine spintronic neurons and synapses, the devices and circuits designed so far do not capture all the desired biological behaviors, and there have been no circuits designed that operate without external silicon-based devices. This interdisciplinary collaborative effort between experiment and circuit design will address these challenges by building and studying circuits using three-terminal magnetic tunnel junction devices. The research will result in design and fabrication of new types of these magnetic devices that more accurately represent the brain's functions, and in measurements of the magnetic devices' behavior in circuits. The project has the potential to establish magnetic materials as a platform for neuromorphic computing, similar to how silicon is the platform material for traditional computing.