Algorithm for Training Neural Networks on Resistive Device Arrays

17 Sep 2019Tayfun GokmenWilfried Haensch

Hardware architectures composed of resistive cross-point device arrays can provide significant power and speed benefits for deep neural network training workloads using stochastic gradient descent (SGD) and backpropagation (BP) algorithm. The training accuracy on this imminent analog hardware however strongly depends on the switching characteristics of the cross-point elements... (read more)

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