Results 41 to 50 of about 1,025,950 (315)
IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023 Matrix-Vector Multiplications (MVMs) represent a heavy workload for both training and inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing (AIMC) systems based on Phase Change Memory (PCM) has been shown to be a valid ...
A. Antolini +11 more
semanticscholar +1 more source
What is a quantum computer, and how do we build one? [PDF]
, 2010 The DiVincenzo criteria for implementing a quantum computer have been seminal in focussing both experimental and theoretical research in quantum information processing.
Kok, Pieter, Perez-Delgado, Carlos A.
core +1 more source
International Journal of Engineering Research and Advanced Technology, 2019 In-memory computing is the storage of information in the main random access memory (RAM) of servers rather than in databases operating on comparatively slow disk drives. It is computing that stores data in RAM across many connected devices and processes it in parallel to speed processing.
Matthew N. O. Sadiku +2 more
openaire +2 more sources
Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU [PDF]
, 2016 In this paper, we present that security threats coming with existing GPU memory management strategy are overlooked, which opens a back door for adversaries to freely break the memory isolation: they enable adversaries without any privilege in a computer ...
Diao, Wenrui +5 more
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Nonvolatile Capacitive Crossbar Array for In‐Memory Computing
Advanced Intelligent Systems, 2022 Conventional resistive crossbar array for in‐memory computing suffers from high static current/power, serious IR drop, and sneak paths. In contrast, the “capacitive” crossbar array that harnesses transient current and charge transfer is gaining attention
Jae Hur +6 more
semanticscholar +1 more source
Neuromorphic, Digital and Quantum Computation with Memory Circuit Elements [PDF]
, 2011 Memory effects are ubiquitous in nature and the class of memory circuit elements - which includes memristors, memcapacitors and meminductors - shows great potential to understand and simulate the associated fundamental physical processes.
Di Ventra, Massimiliano +1 more
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Ultrathin Nitride Ferroic Memory with Large ON/OFF Ratios for Analog In‐Memory Computing
Advances in Materials, 2023 Computing in the analog regime using nonlinear ferroelectric resistive memory arrays can potentially alleviate the energy constraints and complexity/footprint challenges imposed by digital von Neumann systems.
Ding Wang +6 more
semanticscholar +1 more source
Fast and Reconfigurable Logic Synthesis in Memristor Crossbar Array
Advanced Intelligent Systems, 2022 Memristor is a potential basic unit for the in‐memory computing system, which is an approach to break the memory wall of the traditional computer. However, low switching speed, nonuniform device characteristics, and inefficient logic synthesis hinder the
Wei Wang +11 more
doaj +1 more source
Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective [PDF]
, 2019 On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential.
Abbott +56 more
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Advances in Materials, 2021 Ferroelectrics have been demonstrated as excellent building blocks for high‐performance nonvolatile memories, including memristors, which play critical roles in the hardware implementation of artificial synapses and in‐memory computing.
Fei Xue +15 more
semanticscholar +1 more source