Abstract: Aiming at the problem of the low efficiency of coarse granularity data in specific operation mode, the author proposed a data distributed algorithm based on convolutional neural network. Firstly, the convolutional neural network model for coarse granularity data processing was constructed. The connection structure and weight proportion of the neural network in the basic connection layer of the model were given, and the coarse granularity data were trained and pooled. Secondly, the result of training
 pooling was used to solve the minimum loss function of the model and improve the distributed computing ability of the model for coarse granularity data. The experimental results show that in the single machine and cluster mode, the convolutional neural network model has better computing efficiency and data generalization ability.

Key words: convolutional neural network, coarse granularity, convolutional layer, pooling layer