Results 51 to 60 of about 716 (180)

Silicon Nitride Resistive Memories

Advanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source

Demonstration of transfer learning using 14 nm technology analog ReRAM array

Frontiers in Electronics
Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-
Fabia Farlin Athena, Omobayode Fagbohungbe, Nanbo Gong, Malte J. Rasch, Jimmy Penaloza, SoonCheon Seo, Arthur Gasasira, Paul Solomon, Valeria Bragaglia, Steven Consiglio, Hisashi Higuchi, Chanro Park, Kevin Brew, Paul Jamison, Christopher Catano, Iqbal Saraf, Claire Silvestre, Xuefeng Liu, Babar Khan, Nikhil Jain, Steven McDermott, Rick Johnson, I. Estrada-Raygoza, Juntao Li, Tayfun Gokmen, Ning Li, Ruturaj Pujari, Fabio Carta, Hiroyuki Miyazoe, Martin M. Frank, Antonio La Porta, Devi Koty, Qingyun Yang, Robert D. Clark, Kandabara Tapily, Cory Wajda, Aelan Mosden, Jeff Shearer, Andrew Metz, Sean Teehan, Nicole Saulnier, Bert Offrein, Takaaki Tsunomura, Gert Leusink, Vijay Narayanan, Takashi Ando   +45 more
doaj   +1 more source

An Energy-Efficient Digital ReRAM-Crossbar-Based CNN With Bitwise Parallelism

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2017
There is great attention to develop hardware accelerator with better energy efficiency, as well as throughput, than GPUs for convolutional neural network (CNN). The existing solutions have relatively limited parallelism as well as large power consumption
Leibin Ni, Zichuan Liu, Hao Yu, Rajiv V. Joshi   +3 more
doaj   +1 more source

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO2‐Based Memristive Devices

Advanced Electronic Materials, EarlyView.
1T1R‐arrays combining filamentary‐type memristors and CMOS transistors offer great potential for energy‐efficient analog hardware accelerators. Here, transient SET analysis of nanoscale HfO2 memristors integrated on 180 nm CMOS wafers is discussed.
Oliver Artner, Felix Cüppers, Seokki Son, Yang Chen, Xiaohua Liu, Christopher Bengel, Dennis Nielinger, André Zambanini, Stefan Wiefels, Stephan Menzel, Regina Dittmann, Susanne Hoffmann‐Eifert   +11 more
wiley   +1 more source

ReGra: Accelerating Graph Traversal Applications Using ReRAM With Lower Communication Cost

IEEE Access, 2020
There is a growing gap between data explosion speed and the improvement of graph processing systems on conventional architectures. The main reason lies in the large overhead of random access and data movement, as well as the unbalanced and unordered ...
Haoqiang Liu, Qiang-Sheng Hua, Hai Jin, Long Zheng   +3 more
doaj   +1 more source

Integration of Redox‐Active Polyoxovanadate Clusters into PMMA: Structure, Nanoscale Organization and Multilevel Redox Switching

Advanced Electronic Materials, EarlyView.
Solvent‐processable polyoxovanadate–PMMA nanocomposites exhibit concentration‐dependent 2D and 3D organization on gold surfaces, while retaining multilevel redox switching at room temperature. These hybrids bridge nanoscale functionality and macroscopic measurement, establishing a versatile platform for hybrid molecular–polymer memory materials ...
Jonas Lorenz, Marco Moors, Tom Scherzer, Olesya Daikos, Jens Bauer, Andrea Prager, Jan Griebel, Yeji Lee, Vineeth Kumar Bandari, Thomas Blaudeck, Oliver G. Schmidt, Kirill Monakhov   +11 more
wiley   +1 more source

Honey-ReRAM Enabled Sustainable Edge AI System for IoT Applications

IEEE Access
This paper is toward a promising solution to address the environmental sustainability challenge in computing by building brain-inspired and green non-Von Neumann systems with Resistive Random-Access Memory (ReRAM) made from natural organic materials ...
Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md. Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru   +5 more
doaj   +1 more source

Nonlinear Dynamics and Invariants of Motion in ReRAM Cells

Advanced Electronic Materials, EarlyView.
A second‐order cell, hosting one capacitor and two back‐to‐back ReRAMs, admits Invariants of Motion: its states lie on one‐dimensional manifolds at all times. The cell shows quiescent monostability or bistability, depending on the manifold index. At equilibrium, the capacitor voltage vanishes.
Mauro Di Marco, Mauro Forti, Luca Pancioni, Giacomo Innocenti, Alberto Tesi, Alon Ascoli   +5 more
wiley   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

A Fully Integrated System‐on‐Chip Design with Scalable Resistive Random‐Access Memory Tile Design for Analog in‐Memory Computing

Advanced Intelligent Systems, 2022
As the demands of big data applications and deep learning continue to rise, the industry is increasingly looking to artificial intelligence (AI) accelerators.
Fuxi Cai, She-Hwa Yen, Apurva Uppala, Luke Thomas, Tianchi Liu, Peter Fu, Xiaofeng Zhang, Ambrose Low, Deepak Kamalanathan, Joe Hsu, Buvna Ayyagari-Sangamalli   +10 more
doaj   +1 more source