Compact MEOL OxRAM with 14 Conductance Levels for Dense Embedded Inference Computing

A compact 1T1R memory cell with 14 conductance levels is demonstrated in 28nm node technology. The HfO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>-based OxRAM is integrated in the 40nm×40nm drain contact of thin gate oxide Fully Depleted Silicon-On-Insulator (FDSOI) transistors, opening the way towards memory arrays with 0.0357μm2 bitcell area. The OxRAM stack and programming protocols are optimized, resulting in 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> endurance, 2h data retention at 150°C and 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9</sup> read disturb cycles, while keeping low SET currents (30μA) and 1.2V RESET voltages. Furthermore, the pertinence of this OxRAM for Quantized Spiking Neural Network (QSNN) synaptic weight hardware implementation for Automatic Lip-Reading (ALR) inference computing on-chip is elucidated, reaching 74.3% near state-of-art accuracy.

Authors

Institutions

Publication Details

Published
2025-03-30
DOI
https://doi.org/10.1109/irps48204.2025.10983457
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Compact MEOL OxRAM with 14 Conductance Levels for Dense Embedded Inference Computing

T. Dubreuil, J.‐M. Pedini, Amy J. Lambert, Manon Dampfhoffer et al.
1 citations
Advanced Memory and Neural Computing
0.73
article

Compact MEOL OxRAM with 14 Conductance Levels for Dense Embedded Inference Computing

T. Dubreuil, J.‐M. Pedini, Amy J. Lambert, Manon Dampfhoffer, J. Minguet Lopez, C. Comboroure, C. Castan, Sylvain Barraud, F. Andrieu, F. Boulard, A. Souhaité, A. Gharbi
article en
1 citations

Abstract

A compact 1T1R memory cell with 14 conductance levels is demonstrated in 28nm node technology. The HfO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>-based OxRAM is integrated in the 40nm×40nm drain contact of thin gate oxide Fully Depleted Silicon-On-Insulator (FDSOI) transistors, opening the way towards memory arrays with 0.0357μm2 bitcell area. The OxRAM stack and programming protocols are optimized, resulting in 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> endurance, 2h data retention at 150°C and 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9</sup> read disturb cycles, while keeping low SET currents (30μA) and 1.2V RESET voltages. Furthermore, the pertinence of this OxRAM for Quantized Spiking Neural Network (QSNN) synaptic weight hardware implementation for Automatic Lip-Reading (ALR) inference computing on-chip is elucidated, reaching 74.3% near state-of-art accuracy.

Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), CEA Grenoble (FR), Laboratoire d'Électronique des Technologies de l'Information (FR), Université Grenoble Alpes (FR)
Openalex Percentile: Top 28%
Advanced Memory and Neural Computing
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.