Web: http://arxiv.org/abs/2205.01707

May 5, 2022, 1:11 a.m. | Jonathan Kern, Sébastien Henwood, Gonçalo Mordido, Elsa Dupraz, Abdeldjalil Aïssa-El-Bey, Yvon Savaria, François Leduc-Primeau

cs.LG updates on arXiv.org arxiv.org

Memristors enable the computation of matrix-vector multiplications (MVM) in
memory and, therefore, show great potential in highly increasing the energy
efficiency of deep neural network (DNN) inference accelerators. However,
computations in memristors suffer from hardware non-idealities and are subject
to different sources of noise that may negatively impact system performance. In
this work, we theoretically analyze the mean squared error of DNNs that use
memristor crossbars to compute MVM. We take into account both the quantization
noise, due to the …

arxiv dnn dnn accelerators memristor prediction

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