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Paper Detail

Paper IDM.9.4
Paper Title Noisy In-Memory Recursive Computation with Memristor Crossbars
Authors Elsa Dupraz, IMT Atlantique, France; Lav Varshney, University of Illinois at Urbana-Champaign, United States
Session M.9: Topics in Coding for Storage and Memories
Presentation Lecture
Track Coding for Storage and Memories
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract This paper considers iterative dot-product computation implemented on in-memory memristor crossbar substrates. To address the case where true memristor conductance values may differ from their target values, it introduces a theoretical framework that characterizes the effect of conductance value variations on the final computation. For simple dot-products, the final computation error can be approximated by a Gaussian distribution; the mean and variance values of the corresponding Gaussian distribution are provided. For iterative dot-product computation, recursive expressions are derived for the means and variances of the successive computation outputs. Experiments verify the accuracy of the proposed analysis on both synthetic data and on images processed with memristor-based principal component analysis.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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