Achieving Low-Power Analog Resistive Switching in Filamentary Memristive Devices for Energy-Efficient Analog In-Memory Computing.
Sign Up to like & getrecommendations! Published in 2025 at "Small"
DOI: 10.1002/smll.202505708
Abstract: Analog in-memory computing with memristive devices is a promising solution for overcoming energy inefficiencies of traditional Von Neumann architectures, especially in deep learning applications. However, filamentary memristive devices encounter significant challenges, such as high forming… read more here.
Keywords: memristive devices; energy; memory computing; analog memory ... See more keywords
Combined HW/SW Drift and Variability Mitigation for PCM-Based Analog In-Memory Computing for Neural Network Applications
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2023.3241750
Abstract: 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… read more here.
Keywords: pcm based; accuracy; analog memory; memory ... See more keywords
In Situ Analog In-Memory Computing Under Ionizing Radiation Exposure
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Nuclear Science"
DOI: 10.1109/tns.2025.3537985
Abstract: We experimentally performed in situ analog in-memory computing (IMC) under ionizing radiation, using a 40-nm silicon-oxide–nitride-oxide–silicon (SONOS) charge-trap memory array with peripheral circuits that support analog matrix-vector multiplication (MVM) operations. The SONOS array used analog… read more here.
Keywords: situ analog; memory; ionizing radiation; analog memory ... See more keywords