Integrated neuromorphic computing networks by artificial spin synapses and spin neurons
- Integrated neuromorphic computing networks by artificial spin synapses and spin neurons
- 김재욱; 정연주; 김태윤; 양승모; 신정훈; 문경웅; 장가브리엘; 현다슬; 양정엽; 황찬용; 홍진표
- Issue Date
- NPG Asia Materials
- VOL 13, 11
- One long-standing goal in the emerging neuromorphic field is to create a reliable neural network hardware implementation that has low energy consumption, while providing massively parallel computation. Although diverse oxide-based devices have made significant progress as artificial synaptic and neuronal components, these devices still need further optimization regarding linearity, symmetry, and stability. Here, we present a proof-of-concept experiment for integrated neuromorphic computing networks by utilizing spintronics-based synapse (spin-S) and neuron (spin-N) devices, along with linear and symmetric weight responses for spin-S using a stripe domain and activation functions for spin-N. An integrated neural network of electrically connected spin-S and spin-N successfully proves the integration function for a simple pattern classification task. We simulate a spin-N network using the extracted device characteristics and demonstrate a high classification accuracy (over 93%) for the spin-S and spin-N optimization without the assistance of additional software or circuits required in previous reports. These experimental studies provide a new path toward establishing more compact and efficient neural network systems with optimized multifunctional spintronic devices.
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