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Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…

Emerging Technologies · Computer Science 2012-12-17 Victor Erokhin , Gerard David Howard , Andrew Adamatzky

This paper describes a new memristor crossbar architecture that is proposed for use in a high density cache design. This design has less than 10% of the write energy consumption than a simple memristor crossbar. Also, it has up to 4 times…

Hardware Architecture · Computer Science 2013-04-10 Chris Yakopcic , Tarek M. Taha

Edge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Fatima Tuz Zohora , Vedant Karia , Nicholas Soures , Dhireesha Kudithipudi

Practical memristor came into picture just few years back and instantly became the topic of interest for researchers and scientists. Memristor is the fourth basic two-terminal passive circuit element apart from well known resistor,…

Emerging Technologies · Computer Science 2015-06-23 Tejinder Singh

The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific and engineering applications. This paper investigates the…

Mesoscale and Nanoscale Physics · Physics 2025-06-23 Jonathan Lin , Frank Barrows , Francesco Caravelli

In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable…

In-memory computing is an emerging non-von Neumann computing paradigm where certain computational tasks are performed in memory by exploiting the physical attributes of the memory devices. Memristive devices such as phase-change memory…

Emerging Technologies · Computer Science 2020-04-08 Anastasios Petropoulos , Irem Boybat , Manuel Le Gallo , Evangelos Eleftheriou , Abu Sebastian , Theodore Antonakopoulos

Once referred to as the missing circuit component, memristor has come long way across to be recognized and taken as important to future circuit designs. The memristor due to its ability to memorize the state, switch between different…

Emerging Technologies · Computer Science 2016-12-07 Alex Pappachen James

The advent of deep learning has resulted in a number of applications which have transformed the landscape of the research area in which it has been applied. However, with an increase in popularity, the complexity of classical deep neural…

Emerging Technologies · Computer Science 2022-08-24 Venkatesh Rammamoorthy , Geng Zhao , Bharathi Reddy , Ming-Yang Lin

Monolithic three-dimensional integration of memory and logic circuits could dramatically improve performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration,…

Emerging Technologies · Computer Science 2015-09-11 Gina C. Adam , Brian D. Hoskins , Mirko Prezioso , Dmitri B. Strukov

Brain inspired circuits can provide an alternative solution to implement computing architectures taking advantage of fault tolerance and generalisation ability of logic gates. In this brief, we advance over the memristive threshold circuit…

Emerging Technologies · Computer Science 2014-11-20 Alex Pappachen James , Dinesh S. Kumar , Arun Ajayan

Continued progress in high speed computing depends on breakthroughs in both materials synthesis and device architectures. The performance of logic and memory can be enhanced significantly by introducing a memristor, a two terminal device…

Mesoscale and Nanoscale Physics · Physics 2015-04-08 V. K. Sangwan , D. Jariwala , I. S. Kim , K. -S. Chen , T. J. Marks , L. J. Lauhon , M. C. Hersam

Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…

Other Condensed Matter · Physics 2013-07-04 Siddharth Gaba , Patrick Sheridan , Jiantao Zhou , Shinhyun Choi , Wei Lu

Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally…

Emerging Technologies · Computer Science 2015-05-20 Mirko Prezioso , Farnood Merrikh-Bayat , Brian Hoskins , Gina Adam , Konstantin K. Likharev , Dmitri B. Strukov

Memristor-based crossbar arrays represent a promising emerging memory technology to replace conventional memories by offering a high density and enabling computing-in-memory (CIM) paradigms. While analog computing provides the best…

Current advances in emerging memory technologies enable novel and unconventional computing architectures for high-performance and low-power electronic systems, capable of carrying out massively parallel operations at the edge. One emerging…

Emerging Technologies · Computer Science 2018-10-12 Georgios Papandroulidakis , Alexantrou Serb , Ali Khiat , Geoff V. Merrett , Themistoklis Prodromakis

The superior density of passive analog-grade memristive crossbars may enable storing large synaptic weight matrices directly on specialized neuromorphic chips, thus avoiding costly off-chip communication. To ensure efficient use of such…

Emerging Technologies · Computer Science 2019-07-01 Hyungjin Kim , Hussein Nili , Mahmood Mahmoodi , Dmitri Strukov

Passive crossbar arrays based upon memristive devices, at crosspoints, hold great promise for the future high-density and non-volatile memories. The most significant challenge facing memristive device based crossbars today is the problem of…

Emerging Technologies · Computer Science 2015-07-09 Yansong Gao , Omid Kavehei , Damith C. Ranasinghe , Said F. Al-Sarawi , Derek Abbott

The thesis investigates the utilization of memristive and memcapacitive crossbar arrays in low-power machine learning accelerators, offering a comprehensive co-design framework for deep neural networks (DNN). The model, implemented through…

Neural and Evolutionary Computing · Computer Science 2024-03-06 Ankur Singh

As data-intensive applications increasingly strain conventional computing systems, processing-in-memory (PIM) has emerged as a promising paradigm to alleviate the memory wall by minimizing data transfer between memory and processing units.…

Emerging Technologies · Computer Science 2026-02-05 Thomas Neuner , Henriette Padberg , Lior Kornblum , Eilam Yalon , Pedram Khalili Amiri , Shahar Kvatinsky
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