Highly-efficient and scalable TrioN (3N0C) synaptic cell for analog process-in-memory

The development of non-volatile memory (NVM)-based cross-point arrays has paved the way for the realization of neuromorphic architectures toward analog process-in-memory (aPIM). However, the inherent non-ideal characteristics of NVM devices such as asymmetry necessitate capacitor-based synaptic cells. We introduce a capacitorless 3-NMOS 0-capacitor (TrioN, 3N0C) cross-point device, a novel synaptic cell leveraging amorphous indium gallium zinc oxide (a-IGZO), and a promising oxide semiconductor with low off-current. Using only NMOS transistors, TrioN enables high-density arrays with a simplified fabrication process without the need for PMOS or external capacitors. It exhibits excellent switching characteristics, including perfect symmetry, a high on/off ratio, and ultra-fast 10 ns switching. Fabricated hardware demonstrates precise selective updates, supporting 2-cycle updates for improved speed and energy efficiency over conventional 4-cycle methods. Neural network simulations using stochastic gradient descent (SGD) and Tiki-Taka algorithm version 1 (TTv1) on a multi-layer perceptron (MLP) for the MNIST dataset achieve high accuracy of 96.89% and 97.19%, respectively. These results highlight TrioN's potential as a compact, energy-efficient, and scalable solution for neuromorphic computing.

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Publication Details

Journal
Materials Horizons
Published
2025-01-01
DOI
https://doi.org/10.1039/d5mh00324e
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Highly-efficient and scalable TrioN (3N0C) synaptic cell for analog process-in-memory

Hyunjeong Kwak, Jeonghoon Son, Byoungwoo Lee, Seungkun Kim et al.
Materials Horizons
Advanced Memory and Neural Computing
article

Highly-efficient and scalable TrioN (3N0C) synaptic cell for analog process-in-memory

Hyunjeong Kwak, Jeonghoon Son, Byoungwoo Lee, Seungkun Kim, Seyoung Kim, Jun-Yong Lee, Junyoung Choi, Hyejin Kim, Jinho Byun
article en

Abstract

The development of non-volatile memory (NVM)-based cross-point arrays has paved the way for the realization of neuromorphic architectures toward analog process-in-memory (aPIM). However, the inherent non-ideal characteristics of NVM devices such as asymmetry necessitate capacitor-based synaptic cells. We introduce a capacitorless 3-NMOS 0-capacitor (TrioN, 3N0C) cross-point device, a novel synaptic cell leveraging amorphous indium gallium zinc oxide (a-IGZO), and a promising oxide semiconductor with low off-current. Using only NMOS transistors, TrioN enables high-density arrays with a simplified fabrication process without the need for PMOS or external capacitors. It exhibits excellent switching characteristics, including perfect symmetry, a high on/off ratio, and ultra-fast 10 ns switching. Fabricated hardware demonstrates precise selective updates, supporting 2-cycle updates for improved speed and energy efficiency over conventional 4-cycle methods. Neural network simulations using stochastic gradient descent (SGD) and Tiki-Taka algorithm version 1 (TTv1) on a multi-layer perceptron (MLP) for the MNIST dataset achieve high accuracy of 96.89% and 97.19%, respectively. These results highlight TrioN's potential as a compact, energy-efficient, and scalable solution for neuromorphic computing.

Materials HorizonsVol. 12(18)
Pohang University of Science and Technology (KR)
National Research Foundation, Ministry of Trade, Industry and Energy, National Research Foundation of Korea, IC Design Education Center, Ministry of Science and ICT, South Korea
Affordable and clean energy
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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