Results 151 to 160 of about 4,703 (195)

Microscopic KMC Modeling of Oxide RRAMs

2019
We investigate the microscopic behavior of oxide-based resistive random-access memory (RRAM) cells by using a unique three-dimensional (3D) physical simulator. RRAMs are attracting substantial attention and are considered as the next generation of non-volatile memory technologies.
Toufik Sadi, Asen Asenov
openaire   +1 more source

A Study of the Effect of RRAM Reliability Soft Errors on the Performance of RRAM-Based Neuromorphic Systems

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2017
Resistive RAM (RRAM) device has been extensively used as a scalable nonvolatile memory cell in neuromorphic systems due to its several advantages, including its small size and low-power requirements. However, resulting from the stochastic nature of the oxygen vacancies, the RRAM device suffers from reliability soft errors. In this paper, we provide for
Amr M. S. Tosson, Shimeng Yu, Mohab H. Anis, Lan Wei   +3 more
openaire   +1 more source

RRAM, Device, Model and Memory

2022 International Conference on Microelectronics (ICM), 2022
Abdulaziz Alshaya, Qihao Han, Christos Papavassiliou   +2 more
openaire   +1 more source

FPGA Based on Integration of CMOS and RRAM

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2011
In this paper, a novel CMOS-nano hybrid reconfigurable field-prgrammable gate array architecture (rFPGA) is introduced based on resistive memory (RRAM) devices. Different from the existing crossbar-based CMOS-nano architectures, rFPGA consists of mainly 1T1R RRAM structures that can be fabricated by using a CMOS-compatible process.
Sansiri Tanachutiwat, Ming Liu 0022, Wei Wang 0003   +2 more
openaire   +2 more sources

Towards Automotive Grade Embedded RRAM

2018 48th European Solid-State Device Research Conference (ESSDERC), 2018
Most types of resistive RAM (RRAM) explored over the past 20 years have suffered from reliability problems. As a result, RRAM has received relatively little consideration for use in automotive applications. The present article describes an improved subquantum Conductive Bridging RAM (CBRAM®) cell whose reliability appears robust enough for automotive ...
John R. Jameson, John Dinh, Nathan Gonzales, Shane C. Hollmer, Sue Hsu, David Kim, Foroozan Koushan, Derric Lewis, Ed Runnion, Jeffrey Shields, Aaron Tysdal, Daniel Wang, Venkatesh Gopinath   +12 more
openaire   +2 more sources

Device and SPICE modeling of RRAM devices

Nanoscale, 2011
We report the development of physics based models for resistive random-access memory (RRAM) devices. The models are based on a generalized memristive system framework and can explain the dynamic resistive switching phenomena observed in a broad range of devices. Furthermore, by constructing a simple subcircuit, we can incorporate the device models into
Patrick, Sheridan, Kuk-Hwan, Kim, Siddharth, Gaba, Ting, Chang, Lin, Chen, Wei, Lu   +5 more
openaire   +2 more sources

C-RRAM: A Fully Input Parallel Charge-Domain RRAM-based Computing-in-Memory Design with High Tolerance for RRAM Variations

2022 IEEE International Symposium on Circuits and Systems (ISCAS), 2022
Yifan He 0003, Yuxuan Huang, Jinshan Yue, Wenyu Sun, Lu Zhang 0074, Yongpan Liu   +5 more
openaire   +2 more sources

NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators

Science China Information Sciences, 2021
Guangyu Sun, Jingze Liu, Xingchen Li
exaly  

RRAM MATERIALS AND DEVICES

2021
CHU DEWEI, WAN TAO, LI SEAN SUIXIANG
openaire   +4 more sources

PRIVE: Efficient RRAM Programming with Chip Verification for RRAM-based In-Memory Computing Acceleration

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023
Wangxin He, Jian Meng, Sujan Kumar Gonugondla, Shimeng Yu, Naresh R. Shanbhag, Jae-sun Seo   +5 more
openaire   +1 more source