15 papers · ranked by Valyu relevance
Qiao-Feng Ou, Bang-Shu Xiong, Lei Yu, Jing Wen + 2 more
Recent progress in the development of artificial intelligence technologies, aided by deep learning algorithms, has led to an unprecedented revolution in neuromorphic circuits, bringing us ever closer to brain-like computers. However, the vast majority of advanced algorithms still have to run on conventional computers.…
Piergiulio Mannocci, Giacomo Larelli, Marco Bonomi, Daniele Ielmini
Modern workloads challenge von Neumann architectures due to memory-processor data transfer. In-memory computing (IMC) enables in situ processing, with analog IMC (AIMC) based on resistive memories offering high-throughput and energy-efficient multiply-accumulate operations. Precision is limited by noise, device/circuit…
Daniele Ielmini, Giacomo Pedretti
Random-Access Memory (RRAM): Applications and Requirements for Memory and Computing Authors: ['Daniele Ielmini' 'Giacomo Pedretti'] In the information age, novel hardware solutions are urgently needed to efficiently store and process increasing amounts of data. In this scenario, memory devices must evolve significantly…
Alessio Antolini, Francesco Zavalloni, Andrea Lico, Said Quqa + 6 more
'Lorenzo Greco' 'Mauro Mangia' 'Fabio Pareschi' 'Marco Pasotti' 'Eleonora Franchi Scarselli' 'Charith Perera'] Phase Change Memory (PCM) has emerged as a promising non-volatile memory technology with significant applications in both edge computing and analog in-memory computing. This paper synthesizes recent research…
Hong-Zhe Yang, Jian-Peng Dou, Feng Lu, Xiao-Wen Shang + 4 more
In-memory computing, which enables computation directly within memory, represents an efficient approach to processing massively parallel computation tasks that are intractable for conventional computers. However, implementations of in-memory computing have been primarily limited to the classical regime, with its…
Han Bao, Houji Zhou, Jiancong Li, Huaizhi Pei + 12 more
'Ling Yang' 'Shengguang Ren' 'Shaoqin Tong' 'Yi Li' 'Yuhui He' 'Jia Chen' 'Yimao Cai' 'Huaqiang Wu' 'Qi Liu' 'Qing Wan' 'Xiangshui Miao'] With the rapid growth of computer science and big data, the traditional von Neumann architecture suffers the aggravating data communication costs due to the separated structure of…
Yeongkwon Kim, Seung-Bae Jeon, Byung Chul Jang, Jiyan Dai
Memristive logic-in-memory circuits can provide energy- and cost-efficient computing, which is essential for artificial intelligence-based applications in the coming Internet-of-things era. Although memristive logic-in-memory circuits have been previously reported, the logic architecture requiring additional components…
Zhihan Wang, Haiwen Li, Sheng Jiang, Seiichi Miyazaki
Magnetoresistive random-access memory (MRAM), as a promising non-volatile memory technology, has attracted extensive research interest owing to its unique combination of high operating speed, exceptional endurance, low standby power consumption, and CMOS process compatibility. In this review, we provide a comprehensive…
Bobo Tian, Zhuozhuang Xie, Luqiu Chen, Shenglan Hao + 20 more
'Guangdi Feng' 'Xuefeng Liu' 'Hongbo Liu' 'Jing Yang' 'Yuanyuan Zhang' 'Wei Bai' 'Tie Lin' 'Hong Shen' 'Xiangjian Meng' 'Ni Zhong' 'Hui Peng' 'Fangyu Yue' 'Xiaodong Tang' 'Jianlu Wang' 'Qiuxiang Zhu' 'Yachin Ivry' 'Brahim Dkhil' 'Junhao Chu' 'Chungang Duan'] Title: Abstract Analog storage through synaptic weights using…
Guobin Zhang, Xuemeng Fan, Zijian Wang, Pengtao Li + 7 more
Title: Highlights 1. SRMs integrate intrinsic diode-like rectification, enabling sneak path suppression in crossbar arrays without external selectors, simplifying design, and enhancing energy efficiency for high-density in-memory computing. 2. Key metrics such as rectification ratio, nonlinearity, and CMOS…
H. Li, B. Gao, Z. Chen, Y. Zhao + 5 more
'J. Kang'] Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers…
Fan Wang, Jiayi Li, Zhenhan Zhang, Yi Ding + 4 more
'Huawei Chen' 'Peng Zhou'] Title: Summary Driven by technologies such as machine learning, artificial intelligence, and internet of things, the energy efficiency and throughput limitations of the von Neumann architecture are becoming more and more serious. As a new type of computer architecture, computing-in-memory is…
Hasan Erdem Yantır, Ahmed M. Eltawil, Khaled N. Salama
The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial…
Kaiming Cai, Tianli Jin, Wen Siang Lew
Spin-based memory technology is now available as embedded magnetic random access memory (eMRAM) for fast, high-density and non-volatile memory products, which can significantly boost computing performance and ignite the development of new computing architectures.
Yao-Feng Chang
The potential of machine learning and novel computing architecture can be exploited in the immediate future if more efficient hardware is developed that meets the special requirements of bio-inspired computing or unconventional computing schemes. In this area, non-volatile memory (NVM) technology using memristive…