Results 71 to 80 of about 13,298 (199)
Advanced Electronic Materials, EarlyView.This review surveys oxide‐semiconductor devices for in‐memory and neuromorphic computing, highlighting recent progress and remaining challenges in charge‐trap, ferroelectric, and two‐transistor devices. Oxide semiconductors, featuring ultra‐low leakage, low‐temperature processing, and back‐end‐of‐line compatibility, are explored for analog in‐memory ...
Suwon Seong +4 more
wiley +1 more source
RRAM Variability Harvesting for CIM‐Integrated TRNG
Advanced Electronic Materials, EarlyView.This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende +4 more
wiley +1 more source
Dendritic-Inspired Processing Enables Bio-Plausible STDP in Compound Binary Synapses
, 2018 Brain-inspired learning mechanisms, e.g. spike timing dependent plasticity (STDP), enable agile and fast on-the-fly adaptation capability in a spiking neural network. When incorporating emerging nanoscale resistive non-volatile memory (NVM) devices, with
Saxena, Vishal, Wu, Xinyu
core +1 more source
Advanced Electronic Materials, EarlyView.Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
Nanoscale Research Letters, 2023 The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable.
Furqan Zahoor +6 more
doaj +1 more source
Predictability of reset switching voltages in unipolar resistance switching
, 2009 In unipolar resistance switching of NiO capacitors, Joule heating in the conducting channels should cause a strong nonlinearity in the low resistance state current-voltage (I-V) curves.
Chakrabarti B. K. +4 more
core +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization. [PDF]
, 2019 The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product.
Mahmoodi, MR, Prezioso, M, Strukov, DB
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Hafnium carbide formation in oxygen deficient hafnium oxide thin films
, 2016 On highly oxygen deficient thin films of hafnium oxide (hafnia, HfO$_{2-x}$) contaminated with adsorbates of carbon oxides, the formation of hafnium carbide (HfC$_x$) at the surface during vacuum annealing at temperatures as low as 600 {\deg}C is ...
Alff, L. +8 more
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Advanced Intelligent Discovery, EarlyView.Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source