Method and system for optimizing convolutional residual structure of neural network, device, and medium

Abstract

Disclosed is a method for optimizing a convolutional residual structure of a neural network, including: obtaining picture data and convolution kernel data of each group of residual structures from a global memory as inputs, calculating a first convolution to obtain a first result, storing the first result in a shared memory; determining the size of a picture according to the picture data of the first result, dividing the picture into a plurality of first regions, allocating a corresponding block to each first region in the shared memory, calculating a second convolution in the blocks to obtain a second result; determining the size of a second picture, dividing the second picture into a plurality of second regions, allocating each second region to a corresponding block, calculating a third convolution in the blocks to obtain an output; adding the output and the inputs and performing linear rectification to obtain a final result.