Weighted spin torque nano-oscillator system for neuromorphic computing

TY - JOUR

T1 - Weighted spin torque nano-oscillator system for neuromorphic computing

AU - Böhnert, Tim

AU - Rezaeiyan, Yasser

AU - Claro, M. S.

AU - Benetti, L.

AU - Jenkins, A. S.

AU - Farkhani, Hooman

AU - Moradi, Farshad

AU - Ferreira, R.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85185873173&partnerID=8YFLogxK

U2 - 10.1038/s44172-023-00117-9

DO - 10.1038/s44172-023-00117-9

M3 - Journal article

SN - 2731-3395

VL - 2

JO - Nature Communication Engineering

JF - Nature Communication Engineering

M1 - 65

ER -