1. Neuromorphic weighted sum with magnetic skyrmions
- Author
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Gomes, Tristan da Câmara Santa Clara, Sassi, Yanis, Sanz-Hernández, Dédalo, Krishnia, Sachin, Collin, Sophie, Martin, Marie-Blandine, Seneor, Pierre, Cros, Vincent, Grollier, Julie, and Reyren, Nicolas
- Subjects
Computer Science - Emerging Technologies ,Condensed Matter - Materials Science - Abstract
Integrating magnetic skyrmion properties into neuromorphic computing promises advancements in hardware efficiency and computational power. However, a scalable implementation of the weighted sum of neuron signals, a core operation in neural networks, has yet to be demonstrated. In this study, we exploit the non-volatile and particle-like characteristics of magnetic skyrmions, akin to synaptic vesicles and neurotransmitters, to perform this weighted sum operation in a compact, biologically-inspired manner. To this aim, skyrmions are electrically generated in numbers proportional to the input with an efficiency given by a non-volatile weight. These chiral particles are then directed using localized current injections to a location where their presence is quantified through non-perturbative electrical measurements. Our experimental demonstration, currently with two inputs, can be scaled to accommodate multiple inputs and outputs using a crossbar array design, potentially nearing the energy efficiency observed in biological systems., Comment: 12 pages, 5 figures
- Published
- 2023
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