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As conventional memory technologies are challenged by their technological physical limits, emerging technologies driven by novel materials are becoming an attractive option for future memory architectures. Among these technologies,…

Materials Science · Physics 2015-05-28 Omid Kavehei , Said Al-Sarawi , Kyoung-Rok Cho , Kamran Eshraghian , Derek Abbott

Complementary resistive switches (CRS) are considered as a potential solution for the sneak path problem in large-scale integration of passive crossbar resistive memory arrays. A typical CRS is composed of two bipolar memory cells that are…

Materials Science · Physics 2012-05-21 Yuchao Yang , Patrick Sheridan , Wei Lu

This paper presents a novel resistive-only Binary and Ternary Content Addressable Memory (B/TCAM) cell that consists of two Complementary Resistive Switches (CRSs). The operation of such a cell relies on a logic$\rightarrow$ON state…

Resistive Random Access Memory (RRAM) crossbar arrays are an attractive memory structure for emerging nonvolatile memory due to their high density and excellent scalability. Their ability to perform logic operations using RRAM devices makes…

Hardware Architecture · Computer Science 2024-07-16 Arjun Tyagi , Shahar Kvatinsky

Artificial neural networks have become ubiquitous in modern life, which has triggered the emergence of a new class of application specific integrated circuits for their acceleration. ReRAM-based accelerators have gained significant traction…

Signal Processing · Electrical Eng. & Systems 2019-08-14 Jason K. Eshraghian , Sung-Mo Kang , Seungbum Baek , Garrick Orchard , Herbert Ho-Ching Iu , Wen Lei

Deep learning-based recommendation models (DLRMs) are widely deployed in commercial applications to enhance user experience. However, the large and sparse embedding layers in these models impose substantial memory bandwidth bottlenecks due…

Hardware Architecture · Computer Science 2025-09-16 Yu-Hong Lai , Chieh-Lin Tsai , Wen Sheng Lim , Han-Wen Hu , Tei-Wei Kuo , Yuan-Hao Chang

Crossbar arrays using emerging non-volatile memory technologies such as Resistive RAM (ReRAM) offer high density, fast access speed and low-power. However the bandwidth of the crossbar is limited to single-bit read/write per access to avoid…

Emerging Technologies · Computer Science 2016-06-03 Mohammad Nasim Imtiaz Khan , Swaroop Ghosh , Radha Krishna Aluru , Rashmi Jha

In recent times, Resistive RAMs (ReRAMs) have gained significant prominence due to their unique feature of supporting both non-volatile storage and logic capabilities. ReRAM is also reported to provide extremely low power consumption…

Emerging Technologies · Computer Science 2018-09-24 Debjyoti Bhattacharjee , Yaswanth Tavva , Arvind Easwaran , Anupam Chattopadhyay

Resistive random-access memory (RRAM) is gaining popularity due to its ability to offer computing within the memory and its non-volatile nature. The unique properties of RRAM, such as binary switching, multi-state switching, and device…

Emerging Technologies · Computer Science 2024-07-08 Simranjeet Singh , Farhad Merchant , Sachin Patkar

Resistive Switching (RS) is the change in resistance of a dielectric under the influence of an external current or electric field. This change is non-volatile, and the basis of both the memristor and resistive random access memory. In the…

Mesoscale and Nanoscale Physics · Physics 2015-09-30 Paul K. Radtke , Lutz Schimansky-Geier

Crossbar arrays of resistive memories (RRAM) hold the promise of enabling In-Memory Computing (IMC), but essential challenges due to the impact of device imperfection and device endurance have yet to be overcome. In this work, we…

Emerging Technologies · Computer Science 2022-03-04 E. Esmanhotto , T. Hirtzlin , N. Castellani , S. Martin , B. Giraud , F. Andrieu , J. F. Nodin , D. Querlioz , J-M. Portal , E. Vianello

Redox-based nanoionic resistive memory cells (ReRAMs) are one of the most promising emerging nano-devices for future information technology with applications for memory, logic and neuromorphic computing. Recently, the serendipitous…

The increasing computational demand of Convolutional Neural Networks (CNNs) necessitates energy-efficient acceleration strategies. Compute-in-Memory (CIM) architectures based on Resistive Random Access Memory (RRAM) offer a promising…

Signal Processing · Electrical Eng. & Systems 2025-07-25 José Cubero-Cascante , Rebecca Pelke , Noah Flohr , Arunkumar Vaidyanathan , Rainer Leupers , Jan Moritz Joseph

Resistive random access memory (RRAM) is very well known for its potential application in in-memory and neural computing. However, they often have different types of device-to-device and cycle-to-cycle variability. This makes it harder to…

Emerging Technologies · Computer Science 2023-08-08 Rajalekshmi TR , Rinku Rani Das , Chithra R , Alex James

Transistor-based memories are rapidly approaching their maximum density per unit area. Resistive crossbar arrays enable denser memory due to the small size of switching devices. However, due to the resistive nature of these memories, they…

Emerging Technologies · Computer Science 2019-03-06 Mohammed E Fouda , Ahmed M. Eltawil , Fadi Kurdahi

Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from…

Resistive Random Access Memory (ReRAM) is a promising candidate for implementing Computing-in-Memory (CIM) architectures and neuromorphic circuits. ReRAM cells exhibit significant variability across different memristive devices and cycles,…

Resistive random-access memory (ReRAM) is a promising candidate for the next generation non-volatile memory technology due to its simple read/write operations and high storage density. However, its crossbar array structure causes a severe…

Information Theory · Computer Science 2020-10-26 Guanghui Song , Kui Cai , Xingwei Zhong , Jiang Yu , Jun Cheng

Recently Resistive-RAM (RRAM) crossbar has been used in the design of the accelerator of convolutional neural networks (CNNs) to solve the memory wall issue. However, the intensive multiply-accumulate computations (MACs) executed at the…

Signal Processing · Electrical Eng. & Systems 2019-06-10 Xizi Chen , Jingyang Zhu , Jingbo Jiang , Chi-Ying Tsui

Resistive Random-Access Memory (ReRAM) crossbar arrays are promising candidates for in-situ matrix-vector multiplication (MVM), a frequent operation in Deep Learning algorithms. Despite their advantages, these emerging non-volatile memories…

Emerging Technologies · Computer Science 2024-12-05 Benyamin Khezeli , Hamid Reza Zarandi , Elham Cheshmikhani
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