Tencent Technology (shenzhen) Company Limited

Yangming Zhang

Heng Zhang

Jianlin Gao

A data processing method for a convolutional neural network includes: (a) obtaining a matrix parameter of an eigenmatrix; (b) reading corresponding data in an image data matrix from a first buffer space based on the matrix parameter through a first bus, to obtain a next to-be-expanded data matrix, and sending and storing the to-be-expanded data matrix to a second preset buffer space through a second bus; (c) reading the to-be-expanded data matrix, and performing data expansion on the to-be-expanded data matrix to obtain expanded data; (d) reading a preset number of pieces of unexpanded data in the image data matrix, sending and storing the unexpanded data to the second preset buffer space, and updating, based on the unexpanded data, the to-be-expanded data matrix; and (e). repeating (c) and (d) until all data in the image data matrix is completely read out on the to-be-expanded data matrix.

Data processing method and apparatus for convolutional neural network

Embodiments of this application provide a convolution operation processing method and a related product. The integrated chip includes a control unit, at least one convolutional processing element, an input cache, and an output cache. The control unit loads a sectioned convolution kernel and sectioned convolution input data into the input cache, the sectioned convolution kernel being generated by sectioning a convolution kernel and including a plurality of convolution kernel segments, and the sectioned convolution input data being generated by sectioning convolution input data and including a plurality of convolution input data segments; and the at least one convolutional processing element performs a sectioned convolution operation on the sectioned convolution kernel and the sectioned convolution input data to obtain a sectioned convolution result, and stores the sectioned convolution result into the output cache.

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Shenzhen, China

Yangming Zhang