Results 81 to 90 of about 4,641 (217)

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Dendritic-Inspired Processing Enables Bio-Plausible STDP in Compound Binary Synapses

, 2018
Brain-inspired learning mechanisms, e.g. spike timing dependent plasticity (STDP), enable agile and fast on-the-fly adaptation capability in a spiking neural network. When incorporating emerging nanoscale resistive non-volatile memory (NVM) devices, with
Saxena, Vishal, Wu, Xinyu
core   +1 more source

Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing

Advanced Intelligent Systems, EarlyView.
Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang, Jae Seung Woo, Suk‐Kang Sung, Ki‐Whan Song, Woo Young Choi   +4 more
wiley   +1 more source

Device‐Level Implementation of Reservoir Computing With Memristors

Advanced Intelligent Systems, EarlyView.
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley   +1 more source

Field‐free programmable bipolar magnetic heterostructures for neuromorphic computing

InfoMat, EarlyView.
Neuromorphic computing mimics the brain's efficiency, yet typical memristors lack biological synapses' dual signal control. We introduce a magnetic memristor enabling bidirectional, multi‐state modulation without external fields, validated in image feature extraction and neural clustering.
Yaping He, Gaofei Wang, Jinfeng Zhai, Wentao Huang, Zhenyu Zhao, Zheng Zhang, Jiabin Shen, Pan He, Zengguang Cheng, Peng Zhou   +9 more
wiley   +1 more source

Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning

Nature Communications, 2023
In this work, we report the monolithic three-dimensional integration (M3D) of hybrid memory architecture based on resistive random-access memory (RRAM), named M3D-LIME.
Yijun Li, Jianshi Tang, Bin Gao, Jian Yao, Anjunyi Fan, Bonan Yan, Yuchao Yang, Yue Xi, Yuankun Li, Jiaming Li, Wen Sun, Yiwei Du, Zhengwu Liu, Qingtian Zhang, Song Qiu, Qingwen Li, He Qian, Huaqiang Wu   +17 more
doaj   +1 more source

Intrinsic chiroptical responsivity in self‐powered organic photodiodes for polarization‐tunable optical convolution

InfoMat, EarlyView.
Self‐powered chiral organic photodiodes function as polarization‐sensitive convolutional filters for circularly polarized light‐driven optical convolutional neural networks. This conceptually innovative architecture enables dynamic weight modulation, bias‐free operation, and exceptional noise resilience, boosting feature extraction fidelity from 0.15 ...
Lixuan Liu, Weilong Huang, Feihong Zhu, Yongjie Cai, Xiaolong Li, Yang Yang, Xiao Ma, Zhixiang Wei, Wei Chen, Huipeng Chen   +9 more
wiley   +1 more source

A Study of the Variability in Contact Resistive Random Access Memory by Stochastic Vacancy Model

Nanoscale Research Letters, 2018
Variability in resistive random access memory cell has been one of the critical challenges for the development of high-density RRAM arrays. While the sources of variability during resistive switching vary for different transition metal oxide films, the ...
Yun-Feng Kao, Wei Cheng Zhuang, Chrong-Jung Lin, Ya-Chin King   +3 more
doaj   +1 more source

Electromagnetic Analysis of Vertical Resistive Memory with a Sub-nm Thick Electrode

Nanomaterials, 2020
Resistive random access memories (RRAMs) are a type of resistive memory with two metal electrodes and a semi-insulating switching material in-between. As the persistent technology node downscaling continues in transistor technologies, RRAM designers also
Batyrbek Alimkhanuly, Sanghoek Kim, Lok-won Kim, Seunghyun Lee   +3 more
doaj   +1 more source

SiOx-based resistive switching memory integrated in nanopillar structure fabricated by nanosphere lithography [PDF]

, 2014
textA highly compact, one diode-one resistor (1D-1R) SiOx-based resistive switching memory device with nano-pillar architecture has been achieved for the first time using nano-sphere lithography. The average nano-pillar height and diameter are 1.3 μm and
Ji, Li, active 21st century
core