2021
DOI: 10.1109/jxcdc.2021.3119489
|View full text |Cite
|
Sign up to set email alerts
|

NeuroSOFM: A Neuromorphic Self-Organizing Feature Map Heterogeneously Integrating RRAM and FeFET

Abstract: Many currently available hardware implementations of the unsupervised self-organizing feature map (SOFM) algorithm utilize CMOS-only circuits that often compromise key behaviors of the SOFM algorithm due to complexity. We propose a neuromorphic architecture harnessing the unique properties of FeFETs and gated-RRAM for in-memory computing to implement the SOFM algorithm. The FeFET-based synapse, organized in a novel circuit, is able to compute the input-weight Euclidean error in memory via the saturation drain … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 8 publications
(1 citation statement)
references
References 25 publications
0
1
0
Order By: Relevance
“…Implementing SOM with conventional CMOS-based hardware is restricted by the complexity in calculating the ED and winner determination, which imposes an enormous increase in time cost and energy consumption when the number of neurons increases. Until now, several emerging nonvolatile memories, containing resistive random access memory (RRAM) and ferroelectric field-effect transistor (FeFET), were proposed as synaptic devices to implement SOM neuromorphic systems [3]- [7]. However, compared with these devices, 3D NAND Flash has obvious advantages in terms of cost, retention, density, and technology maturity [8]- [10].…”
Section: Introductionmentioning
confidence: 99%
“…Implementing SOM with conventional CMOS-based hardware is restricted by the complexity in calculating the ED and winner determination, which imposes an enormous increase in time cost and energy consumption when the number of neurons increases. Until now, several emerging nonvolatile memories, containing resistive random access memory (RRAM) and ferroelectric field-effect transistor (FeFET), were proposed as synaptic devices to implement SOM neuromorphic systems [3]- [7]. However, compared with these devices, 3D NAND Flash has obvious advantages in terms of cost, retention, density, and technology maturity [8]- [10].…”
Section: Introductionmentioning
confidence: 99%