Results 31 to 40 of about 2,956 (211)

Multi-ReRAM synapses for artificial neural network training

, 2019
Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges.
Piveteau, Christophe, Manuel Le Gallo, Yusuf Leblebici, Le Gallo, Manuel, Cecilia Giovinazzo, Krawczuk, Igor, Igor Krawczuk, Abu Sebastian, Leblebici, Yusuf, Boybat, Irem, Eleftheriou, Evangelos, Giannopoulos, Jason, Iason Giannopoulos, Carlo Ricciardi, Evangelos Eleftheriou, Elmira Shahrabi, Sebastian, Abu, Ricciardi, Carlo, Christophe Piveteau, Shahrabi, Elmira, Giovinazzo, Cecilia, Irem Boybat, Ricciardi C., Shahrabi E., Leblebici Y., Sebastian A., Giannopoulos I., Piveteau C., Giovinazzo C., Eleftheriou E., Krawczuk I., Boybat I., Le Gallo M.   +32 more
core   +2 more sources

Analog Weights in ReRAM DNN Accelerators [PDF]

2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2019
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, 5 pages, 4 ...
Jason Kamran Eshraghian, Sung-Mo Kang 0001, Seungbum Baek, Garrick Orchard, Herbert Ho-Ching Iu, Wen Lei   +5 more
openaire   +3 more sources

PRAP-PIM: A weight pattern reusing aware pruning method for ReRAM-based PIM DNN accelerators

High-Confidence Computing, 2023
Resistive Random-Access Memory (ReRAM) based Processing-in-Memory (PIM) frameworks are proposed to accelerate the working process of DNN models by eliminating the data movement between the computing and memory units.
Zhaoyan Shen, Jinhao Wu, Xikun Jiang, Yuhao Zhang, Lei Ju, Zhiping Jia   +5 more
doaj   +1 more source

NEXAFS study of electronic and atomic structure of active layer in Al/indium tin oxide/TiO2 stack during resistive switching

Science and Technology of Advanced Materials, 2016
We have studied the stability of the resistive switching process in the Al/(In2O3)0.9(SnO2)0.1/TiO2 assembly grown by atomic layer deposition. Besides electrical characterization the effect of electric field on the atomic electronic structure of the TiO2
Elena Filatova, Aleksei Konashuk, Yuri Petrov, Evgeny Ubyivovk, Andrey Sokolov, Andrei Selivanov, Victor Drozd   +6 more
doaj   +1 more source

ReDy: A Novel ReRAM-centric Dynamic Quantization Approach for Energy-efficient CNN Inference [PDF]

, 2023
The primary operation in DNNs is the dot product of quantized input activations and weights. Prior works have proposed the design of memory-centric architectures based on the Processing-In-Memory (PIM) paradigm.
González, Antonio, Sabri, Mohammad, Riera, Marc   +2 more
core   +1 more source

ARIA: Additive ReRAM-Based Integrity and Aging Monitoring for ICs

IEEE Access
This paper reports an approach for monitoring aging and integrity of CMOS circuits through additively manufactured Resistive Random-Access Memory (ReRAM) based test structures.
Thomas Schultz, Rashmi Jha, Brian Dupaix, Matt Casto   +3 more
doaj   +1 more source

Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions

IEEE Open Journal of Circuits and Systems
The high speed, scalability, and parallelism offered by ReRAM crossbar arrays foster the development of ReRAM-based next-generation AI accelerators. At the same time, the sensitivity of ReRAM to temperature variations decreases $\text{R}_{ON}/\text{R}_ ...
Kamilya Smagulova, Mohammed E. Fouda, Ahmed Eltawil   +2 more
doaj   +1 more source

Optimal Design of FPGA Switch Matrix with Ion Mobility Based Nonvolatile ReRAM

Discrete Dynamics in Nature and Society, 2015
There are high demands for research of new device with greater accessing speed and stability to replace the current SRAM storage cell. The resistive random access memory (ReRAM) is a metal oxide which is based on nonvolatile memory device possessing the ...
Peng Hai-yun, Zhou Wen-gang
doaj   +1 more source

Kernel Application of the Stacked Crossbar Array Composed of Self‐Rectifying Resistive Switching Memory for Convolutional Neural Networks

Advanced Intelligent Systems, 2020
Herein, a feasible method is provided for circuit implementation of the convolutional neural network (CNN) in neuromorphic hardware using the multiple layers‐stacked resistance switching random access memory (ReRAM).
Yumin Kim, Jihun Kim, Seung Soo Kim, Young Jae Kwon, Gil Seop Kim, Jeong Woo Jeon, Dae Eun Kwon, Jung Ho Yoon, Cheol Seong Hwang   +8 more
doaj   +1 more source

Sequence learning in a spiking neuronal network with memristive synapses

Neuromorphic Computing and Engineering, 2023
Brain-inspired computing proposes a set of algorithmic principles that hold promise for advancing artificial intelligence. They endow systems with self learning capabilities, efficient energy usage, and high storage capacity.
Younes Bouhadjar, Sebastian Siegel, Tom Tetzlaff, Markus Diesmann, Rainer Waser, Dirk J Wouters   +5 more
doaj   +1 more source