Results 101 to 110 of about 4,276 (120)

Self-assembled 2D finned covellite (CuS) for resistive RAM

Applied Physics Letters, 2018
Copper sulfides (Cu2−xS) comprises a family of sulfides which possess good electrical and photovoltaic properties due to their self-doping (p-type) nature, attributed from the copper vacancies in their structure.
Zhen Quan Cavin Ng, Royston Tan, A. Rath, A. Wee, D. Chua   +4 more
semanticscholar   +1 more source

ReCAM: Resistive RAM Digital Content Addressable Memory Using Novel 3T1R Bitcell

IEEE Electron Devices Technology and Manufacturing Conference
The demands of data-intensive applications necessitate solutions that are high-speed and energy-efficient and deliver superior performance. Non-volatile memory devices, such as Resistive Random Access Memory (ReRAM), have emerged as promising options for
Radheshyam Sharma, Narendra Singh Dhakad, Govindu Sathvik Reddy, Vishal Sharma, S. Vishvakarma   +4 more
semanticscholar   +1 more source

In-Memory Computation Using CMOS-Integrated Resistive RAM for Robotic Navigation

International Conference on Systems
Neuromorphic and in-memory computing (IMC) enabled by Resistive Random Access Memory (ReRAM) holds the potential to dramatically improve the energy efficiency of computation.
Jeelka Solanki, Jacob Pelton, Rocco D. Febbo, Maximilian Liehr, Andrew DeCandia, K. Beckmann, Garrett S. Rose, Nathaniel C. Cady   +7 more
semanticscholar   +1 more source

Fabrication and Characterization of Alumina Based Resistive RAM for Space Applications

2024 IEEE 24th International Conference on Nanotechnology (NANO)
In this paper, we have studied resistive random-access memory (ReRAM) which inherits excellent properties as a non-volatile memory in terms of higher speed, lower cost, higher storage density and scalability for applications in various fields.
Dharmendra Kumar Panday, Saket Suman, Saif Khan, A. Srivastva   +3 more
semanticscholar   +1 more source

Cryogenic Analog 1T-ReRAM with Enhanced Dynamic Range and Suppressed Noise for Cold Neural Networks

International Electron Devices Meeting
We present the first cryogenic characterization of read noise in 14 nm CMOS compatible analog resistive RAMs (ReRAMs) and evaluate the efficiency of analog in-memory (AIM) neural network (NN) training at 77 K using the optimized Tiki-Taka algorithm (TTv2)
M. S. Ram, D. Lombardo, E. Zaccaria, D. Falcone, T. Stecconi, A. L. Porta, M. Sousa, S. Reidt, A. Ferraris, C. Zota, V. Bragaglia, B. Offrein   +11 more
semanticscholar   +1 more source

Test and Calibration Methods for Process Variation of ReRAM-based Spiking Neural Networks

International Test Conference
Spiking Neural Networks (SNNs) implemented with Resistive RAM (ReRAM) offer promising advantages in area and power efficiency due to their compatibility with compute-in-memory architectures.
Po-Sheng Chiu, Chih-Yu Hsu, Chih-Tsun Huang, Jing-Jia Liou   +3 more
semanticscholar   +1 more source

ReRAM-Based In-Memory Computation for Matrix Multiplication and Perceptron-Based Logic

2025 International Conference on Advancements in Power, Communication and Intelligent Systems (APCI)
Resistive RAM (ReRAM)-based in-memory computing (IMC) is a promising alternative to traditional architectures for achieving energy-efficient and high-performance computing.
Bristo C J, Safvan C K, G. S. Kumar, Suryagayatri Thangalazhi, Adersh V R   +4 more
semanticscholar   +1 more source

HotReRAM: A Performance-Power–Thermal Simulation Framework for ReRAM-Based Caches

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
This article proposes a comprehensive thermal modeling and simulation framework, HotReRAM, for resistive RAM (ReRAM)-based caches that is verified against a memristor circuit-level model.
Shounak Chakraborty, Thanasin Bunnam, Jedsada Arunruerk, Sukarn Agarwal, Shengqi Yu, R. Shafik, Magnus Själander   +6 more
semanticscholar   +1 more source

Read Noise Analysis in Analog Conductive-Metal-Oxide/HfOx ReRAM Devices

Device Research Conference
Analog in-memory computing with resistive memory devices is a compelling alternative to conventional digital von Neumann computers [1]. Recent advancements in learning algorithms and hardware optimizations have enabled the utilization of ReRAM technology
D. Lombardo, M. Ram, T. Stecconi, W. Choi, A. L. Porta, D. Falcone, B. Offrein, V. Bragaglia   +7 more
semanticscholar   +1 more source

FARe: Fault-Aware GNN Training on ReRAM-Based PIM Accelerators

Design, Automation and Test in Europe
Resistive random-access memory (ReRAM)-based processing-in-memory (PIM) architecture is an attractive solution for training Graph Neural Networks (GNNs) on edge platforms.
Pratyush Dhingra, Chukwufumnanya Ogbogu, B. K. Joardar, J. Doppa, Anantharaman Kalyanaraman, P. Pande   +5 more
semanticscholar   +1 more source