Abstract
Spintronics and magnetic materials exhibit many physical phenomena that are promising for implementing neuromorphic computing natively in hardware. Here, we review the current state-of-the-art, focusing on the areas of spintronic synapses, neurons, and neural networks. Many current implementations are based on the paradigm of reservoir computing, where the details of the network do not need to be known but where significant post-processing is needed. Benchmarks are given where possible. We discuss the scientific and technological advances needed to bring about spintronic neuromorphic computing that could be useful to an end-user in the medium term.
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