Digital in-memory stochastic computing architecture for vector-matrix multiplication

Digital in-memory stochastic computing architecture for vector-matrix multiplication

The applications of the Artificial Intelligence are currently dominating the technology landscape. Meanwhile, the conventional Von Neumann architectures are struggling with the data-movement bottleneck to meet the ever-increasing performance demands of these data-centric applications. Moreover, The...

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Bibliographic Details
Main Authors:	Shady Agwa, Themis Prodromakis
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2023-07-01
Series:	Frontiers in Nanotechnology
Subjects:	stochastic computing in-memory computing beyond von-neumann architectures vector-matrix multiplication RRAM deep neural network
Online Access:	https://www.frontiersin.org/articles/10.3389/fnano.2023.1147396/full

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