TRAINING CONVOLUTIONAL NEURAL NETWORK ON GRAPHICS PROCESSING UNITS

摘要

FIELD: information technology.;SUBSTANCE: method comprises the following steps: receiving graphics data representing a state of the convolutional neural network and comprising one or more textures representing one or more neural network variables, wherein said textures comprise a texture with two-dimensional addressing, and at least one of the textures represents a neural network variable with addressing of more than two dimensions which has been flattened into two dimensional addressing, the convolutional neural network comprising at least one layer comprising a plurality of patches; executing one or more programs on the graphics processing unit (GPU) in order to perform a forward pass in the convolutional neural network, executing one or more programs to perform a backward pass in the convolutional neural network, the executing including performing convolution operations on the patches; executing one or more programs in order to modify the patches in the convolutional neural network by changing the graphics data based on results of the backward pass; and repeating execution of one or more programs to perform forward passes, backward passes, and to modify the graphics data until the convolutional neural network is trained.;EFFECT: lower computational complexity.;17 cl, 9 dwg