Weighted Spin Torque Nano-Oscillator System for Neuromorphic Computing

Abstract

Abstract Here we show the weighted spin torque nano-oscillator (WSTNO) as a programmable building block for the next-generation neuromorphic computing systems. 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. Both MTJ types are fabricated from a multifunctional MTJ stack in a single fabrication process, which allows close proximity of the devices, reduces the footprint and is compatible with monolithic integration on top of CMOS technology. The non-linear output based on the weighted sum of the inputs is demonstrated in a proof-of-principle implementation of the WSTNO using three MTJs. The oscillator shows an output power above 3 µW and frequencies of 240 MHz. Multidisciplinary: physics, material science, electrical engineering, spintronics, neuromorphic computation