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.
Authors
- Hyunjeong Kwak (ORCID: https://orcid.org/0009-0008-8814-1823)
- Jeonghoon Son (ORCID: https://orcid.org/0009-0003-4281-6614)
- Byoungwoo Lee
- Seungkun Kim (ORCID: https://orcid.org/0009-0004-1378-0699)
- Seyoung Kim (ORCID: https://orcid.org/0000-0002-0408-1165)
- Jun-Yong Lee (ORCID: https://orcid.org/0009-0007-7654-0643)
- Junyoung Choi (ORCID: https://orcid.org/0009-0003-5221-2988)
- Hyejin Kim (ORCID: https://orcid.org/0009-0002-7748-2100)
- Jinho Byun
Institutions
- Pohang University of Science and Technology (KR)
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
Funders
- 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