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As the compute demands for machine learning and artificial intelligence applications continue to grow, neuromorphic hardware has been touted as a potential solution. New emerging devices like memristors, atomic switches, etc have shown…

Emerging Technologies · Computer Science 2020-09-24 Natesh Ganesh

High-voltage CMOS (HV-CMOS) pixel technology is being considered for future Higgs factory experiments. The ATLASPix3.1 chip, with a pitch of 50$\mu m$ x 150$\mu m$, fabricated using TSI 180nm HV-CMOS technology, is a full reticle-size…

Instrumentation and Detectors · Physics 2025-02-18 F. Ustuner , R. Zanzottera , A. Andreazza , R. Dong , H. Fox , Y. Gao , P. Gheewalla , B. Masic , L. Meng , I. Peric , F. Sabatini

CMOS pixel sensors (CPS) represent a novel technological approach to building charged particle detectors. CMOS processes allow to integrate a sensing volume and readout electronics in a single silicon die allowing to build sensors with a…

This article is present high precision multiwave rectifier circuit operating in low voltage plus or minus 1.5 Volt current modes by CMOS technology 0.5 \mum, receive input and give output in current mode, respond at high frequency period.…

Other Computer Science · Computer Science 2010-01-14 Bancha Burapattanasiri

Resistive random access memory (RRAM) is a promising candidate for next-generation nonvolatile memory (NVM) and in-memory computing applications. Compact models are essential for analyzing the circuit and system-level performance of…

Emerging Technologies · Computer Science 2025-11-12 Akif Hamid , Orchi Hassan

Compact models of memristors are essential for simulating large-scale neuromorphic systems, yet they often do not include description of complex dynamics like volatile relaxation and synaptic plasticity. We introduce a modular,…

Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage…

Emerging Technologies · Computer Science 2025-01-22 Sahitya Yarragolla , Torben Hemke , Fares Jalled , Tobias Gergs , Jan Trieschmann , Tolga Arul , Thomas Mussenbrock

Extracellular, large scale in vivo recording of neural activity is mandatory for elucidating the interaction of neurons within large neural networks at the level of their single unit activity. Technological achievements in MEMS-based…

Neurons and Cognition · Quantitative Biology 2017-07-03 Patrick Ruther , Oliver Paul

This paper describes a multi-functional deep in-memory processor for inference applications. Deep in-memory processing is achieved by embedding pitch-matched low-SNR analog processing into a standard 6T 16KB SRAM array in 65 nm CMOS. Four…

Hardware Architecture · Computer Science 2016-10-25 Mingu Kang , Sujan Gonugondla , Ameya Patil , Naresh Shanbhag

This paper presents the analysis of an efficient alternative interface circuit for MEMS electrostatic energy harvesters. It is entirely composed by diodes and capacitors. Based on modeling and simulation, the anti-phase gap-closing…

Applied Physics · Physics 2017-09-27 Binh Duc Truong , Cuong Phu Le , Einar Halvorsen

Memristive systems are generalisations of memristors, which are resistors with memory. In this paper, we present a quantum description of memristive systems. Using this model we propose and experimentally demonstrate a simple and practical…

Mesoscale and Nanoscale Physics · Physics 2017-09-11 Ying Li , Gregory W. Holloway , Simon C. Benjamin , G. Andrew D. Briggs , Jonathan Baugh , Jan A. Mol

The advent of nanoscale memristors raised hopes of being able to build CMOL (CMOS/nanowire/moLecular) type ultra-dense in-memory-computing circuit architectures. In CMOL, nanoscale memristors would be fabricated at the intersection of…

Emerging Technologies · Computer Science 2022-09-14 L. A. Camuñas-Mesa , E. Vianello , C. Reita , T. Serrano-Gotarredona , B. Linares-Barranco

On-chip memory (usually based on Static RAMs-SRAMs) are crucial components for various computing devices including heterogeneous devices, e.g., GPUs, FPGAs, ASICs to achieve high performance. Modern workloads such as Deep Neural Networks…

Hardware Architecture · Computer Science 2022-07-20 İsmail Emir Yüksel , Behzad Salami , Oğuz Ergin , Osman Sabri Ünsal , Adrian Cristal Kestelman

Emerging non-volatile memories (NVMs) represent a disruptive technology that allows a paradigm shift from the conventional von Neumann architecture towards more efficient computing-in-memory (CIM) architectures. Several instrumentation…

Memristors have been at the forefront of nanoelectronics research for the last decade, offering a valuable component to reconfigurable computing. Their attributes have been studied extensively along with applications that leverage their…

Memristors are prominent passive circuit elements with promising futures for energy-efficient in-memory processing and revolutionary neuromorphic computation. State-of-the-art memristors based on two-dimensional (2D) materials exhibit…

Computational Physics · Physics 2023-03-14 Samuel Aldana , Jakub Jadwiszczak , Hongzhou Zhang

Programmable photonic integrated circuits are expected to play an increasingly important role to enable high-bandwidth optical interconnects, and large-scale in-memory computing as needed to support the rise of artificial intelligence and…

Optics · Physics 2024-12-11 Jayita Dutta , Rui Chen , Virat Tara , Arka MAjumdar

We extend the notion of memristive systems to capacitive and inductive elements, namely capacitors and inductors whose properties depend on the state and history of the system. All these elements show pinched hysteretic loops in the two…

Mesoscale and Nanoscale Physics · Physics 2009-11-21 Massimiliano Di Ventra , Yuriy V. Pershin , Leon O. Chua

Currently, memristor devices suffer from variability between devices and from cycle to cycle. In this work, we study the impact of device variations on memristive Material Implication (IMPLY). New constraints for different parameters and…

Emerging Technologies · Computer Science 2021-01-19 Simon Michael Laube , Nima TaheriNejad

In the quest for alternatives to traditional CMOS, it is being suggested that digital computing efficiency and power can be improved by matching the precision to the application. Many applications do not need the high precision that is…

Machine Learning · Computer Science 2014-10-17 Juan Pablo Carbajal , Joni Dambre , Michiel Hermans , Benjamin Schrauwen