Results 1 to 10 of about 134 (108)

A Relaxed Quantization Training Method for Hardware Limitations of Resistive Random Access Memory (ReRAM)-Based Computing-in-Memory [PDF]

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020
Nonvolatile computing-in-memory (nvCIM) exhibits high potential for neuromorphic computing involving massive parallel computations and for achieving high energy efficiency.
Wei-Chen Wei, Chuan-Jia Jhang, Yi-Ren Chen, Cheng-Xin Xue, Syuan-Hao Sie, Jye-Luen Lee, Hao-Wen Kuo, Chih-Cheng Lu, Meng-Fan Chang, Kea-Tiong Tang   +9 more
doaj   +2 more sources

The Spectral Response of the Dual Microdisk Resonator Based on BaTiO₃ Resistive Random Access Memory

Micromachines, 2022
With the resistive random access memory (ReRAM) devices based on the Al/BaTiO3 (BTO)/ITO structure fabricated at hand, by cross-analyzing the resistive memory characteristics in terms of various barium titanate (BTO) film thicknesses, it is found that ...
Ricky Wenkuei Chuang, Bo-Liang Liu, Cheng-Liang Huang   +2 more
doaj   +1 more source

Fabrication of a Hole‐Type Vertical Resistive‐Switching Random‐Access Array and Intercell Interference Induced by Lateral Charge Spreading

Advanced Electronic Materials, 2023
A hole‐type vertical structure is adopted to fabricate a vertically stacked resistive switching random access memory (ReRAM) array. The vertical configuration is more advantageous in lowering the process cost and increasing integration density than the ...
Seung Soo Kim, Soo Kyeom Yong, Jihun Kim, Jin Myung Choi, Tae Won Park, Hyun Young Kim, Hae Jin Kim, Cheol Seong Hwang   +7 more
doaj   +1 more source

Conductance-Aware Quantization Based on Minimum Error Substitution for Non-Linear-Conductance-State Tolerance in Neural Computing Systems

Micromachines, 2022
Emerging resistive random-access memory (ReRAM) has demonstrated great potential in the achievement of the in-memory computing paradigm to overcome the well-known “memory wall” in current von Neumann architecture.
Chenglong Huang, Nuo Xu, Wenqing Wang, Yihong Hu, Liang Fang   +4 more
doaj   +1 more source

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

High-Quality Single-Crystalline β-Ga₂O₃ Nanowires: Synthesis to Nonvolatile Memory Applications

Nanomaterials, 2021
One of the promising nonvolatile memories of the next generation is resistive random-access memory (ReRAM). It has vast benefits in comparison to other emerging nonvolatile memories.
Chandrasekar Sivakumar, Gang-Han Tsai, Pei-Fang Chung, Babu Balraj, Yen-Fu Lin, Mon-Shu Ho   +5 more
doaj   +1 more source

A Reconfigurable 4T2R ReRAM Computing In-Memory Macro for Efficient Edge Applications

IEEE Open Journal of Circuits and Systems, 2021
Resistive random access memory (ReRAM)-based computing in-memory (CIM) is a promising solution to overcome the von-Neumann bottleneck in conventional computing architectures. We propose a reconfigurable ReRAM architecture using a novel 4T2R bit-cell that
Yuzong Chen, Lu Lu, Bongjin Kim, Tony Tae-Hyoung Kim   +3 more
doaj   +1 more source

Single Event Upsets Under Proton, Thermal, and Fast Neutron Irradiation in Emerging Nonvolatile Memories

IEEE Access, 2022
In New Space, the need for reduced cost, higher performance, and more prompt delivery plans in radiation-harsh environments have motivated spacecraft designers to use Commercial-Off-The-Shelf (COTS) memories and emerging technology devices.
Golnaz Korkian, Daniel Leon, Francisco J. Franco, Juan C. Fabero, Manon Letiche, Yolanda Morilla, Pedro Martin-Holgado, Helmut Puchner, Hortensia Mecha, Juan A. Clemente   +9 more
doaj   +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

Medium-Temperature-Oxidized GeO x Resistive-Switching Random-Access Memory and Its Applicability in Processing-in-Memory Computing

Nanoscale Research Letters, 2022
Processing-in-memory (PIM) is emerging as a new computing paradigm to replace the existing von Neumann computer architecture for data-intensive processing. For the higher end-user mobility, low-power operation capability is more increasingly required and
Kannan Udaya Mohanan, Seongjae Cho, Byung-Gook Park   +2 more
doaj   +1 more source