Convolutional neural networks using resistive processing unit array

Technical solutions are described for implementing a convolutional neural network (CNN) using resistive processing unit (RPU) array. An example method includes configuring an RPU array corresponding to a convolution laye

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Technical solutions are described for implementing a convolutional neural network (CNN) using resistive processing unit (RPU) array. An example method includes configuring an RPU array corresponding to a convolution layer in the CNN based on convolution kernels of the layer. The method further includes performing forward pass computations via the RPU array by transmitting voltage pulses corresponding to input data to the RPU array, and storing values corresponding to output currents from the RPU arrays as output maps. The method further includes performing backward pass computations via the RPU array by transmitting voltage pulses corresponding to error of the output maps, and storing the output currents from the RPU arrays as backward error maps. The method further includes performing update pass computations via the RPU array by transmitting voltage pulses corresponding to the input data of the convolution layer and the error of the output maps to the RPU array.