Weighted spin torque nano-oscillator system for neuromorphic computing

Neuromorphic computing is a promising strategy to overcome fundamental limitations, such as enormous power consumption, by massive parallel data processing, similar to the brain. Here we demonstrate a proof-of-principle implementation of the weighted spin torque nano-oscillator (WSTNO) as a programmable building block for the next-generation neuromorphic computing systems (NCS). The WSTNO is a spintronic circuit composed of two spintronic devices made of magnetic tunnel junctions (MTJs): non-volatile magnetic memories acting as synapses and non-linear spin torque nano-oscillator (STNO) acting as a neuron. The non-linear output based on the weighted sum of the inputs is demonstrated using three MTJs. The STNO shows an output power above 3 µW and frequencies of 240 MHz. Both MTJ types are fabricated from a multifunctional MTJ stack in a single fabrication process, which reduces the footprint, is compatible with monolithic integration on top of CMOS technology and paves ways to fabricate more complex neuromorphic computing systems.

T. Böhnert, Y. Rezaeiyan, M. S. Claro, L. Benetti, A. S. Jenkins, H. Farkhani, F. Moradi, R. Ferreira