Results 271 to 280 of about 1,025,950 (315)

In-memory computing with ferroelectrics

Nature Electronics, 2020
Non-linear ferroelectric tunnel junctions could be used to create low-power in-memory computing systems.
openaire   +1 more source

A Concealable RRAM Physical Unclonable Function Compatible with In-Memory Computing

Design, Automation and Test in Europe
Resistive random access memory (RRAM) has been widely used in physical unclonable function (PUF) design due to its low power consumption, fast read/write speed, and significant intrinsic randomness.
Jiang Li, Yijun Cui, Chenghua Wang, Weiqiang Liu, Shahar Kvatinsky   +4 more
semanticscholar   +1 more source

IMCE: An In-Memory Computing and Encrypting Hardware Architecture for Robust Edge Security

Design, Automation and Test in Europe
Edge devices deployed in unsupervised scenarios employ Physical Unclonable Functions (PUFs) for identity authentication and embedded XOR encoding for data encryption.
Hanyong Shao, Boyi Fu, Jinghao Yang, Wenpu Luo, Chang Su, Zhiyuan Fu, Kechao Tang, Ru Huang   +7 more
semanticscholar   +1 more source

Hyperspectral In-Memory Computing

Optical Fiber Communication Conference (OFC) 2024
We propose and demonstrate hyperspectral in-memory computing systems that harness both frequency and space dimensions, utilizing optical frequency combs and programmable optical memories. This approach offers the potential for energy-efficient optical information processing beyond PetaOPS-level performance.
Mostafa Honari Latifpour, Byoung Jun Park, Yoshihisa Yamamoto, Myoung-Gyun Suh   +3 more
openaire   +1 more source

In-Memory Computing: The Next-Generation AI Computing Paradigm

Proceedings of the 2020 on Great Lakes Symposium on VLSI, 2020
To overcome the memory bottleneck of von-Neuman architecture, various memory-centric computing techniques are emerging to reduce the latency and energy consumption caused by data communication. The great success of artificial intelligence (AI) algorithms, which involve a large number of computations and data movements, has motivated and accelerated the
Yufei Ma, Yuan Du, Li Du, Jun Lin, Zhongfeng Wang   +4 more
openaire   +1 more source

A crossbar array of magnetoresistive memory devices for in-memory computing

Nature, 2022
Seungchul Jung, Hyungwoo Lee, Sungmeen Myung, Hyunsoo Kim, Seung Keun Yoon, Soonwan Kwon, Yongmin Ju, Minje Kim, Wooseok Yi, Shinhee Han, B. Kwon, B. Seo, Kilho Lee, G. Koh, Kangho Lee, Yoonjong Song, Changkyu Choi, Do-Hyun Ham, Sang Joon Kim   +18 more
semanticscholar   +1 more source

An in-memory computing architecture based on a duplex two-dimensional material structure for in situ machine learning

Nature Nanotechnology, 2023
Hongkai Ning, Zhihao Yu, Qingtian Zhang, Hengdi Wen, B. Gao, Yun Mao, Yuankun Li, Ying Zhou, Yue Zhou, Jiewei Chen, Lei Liu, Wenfeng Wang, Taotao Li, Yating Li, Wanqing Meng, Weisheng Li, Yun Li, Hao Qiu, Yi Shi, Yang Chai, Huaqiang Wu, Xinran Wang   +21 more
semanticscholar   +1 more source

A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing

IEEE International Solid-State Circuits Conference, 2021

semanticscholar   +1 more source

An ultrafast bipolar flash memory for self-activated in-memory computing

Nature Nanotechnology, 2023
Xiaohe Huang, Chunsen Liu, Zhaowu Tang, Senfeng Zeng, Shuiyuan Wang, Peng Zhou   +5 more
semanticscholar   +1 more source

In-Memory-Computing

2023
Saeideh Shirinzadeh, Rolf Drechsler
openaire   +1 more source