Reservoir Computing with Planar Nanomagnet Arrays
This work addresses the need for dedicated neuromorphic hardware in size, weight, and power constrained environments, though it appears incremental as it applies an existing method to a new hardware type.
The paper tackled the problem of implementing reservoir computing in hardware for neuromorphic applications by proposing a planar nanomagnet array, achieving 100% accuracy in identifying simple waveforms in simulations.
Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments. This work proposes a novel hardware implementation of a reservoir computer using a planar nanomagnet array. A small nanomagnet reservoir is demonstrated via micromagnetic simulations to be able to identify simple waveforms with 100% accuracy. Planar nanomagnet reservoirs are a promising new solution to the growing need for dedicated neuromorphic hardware.