Review of Deep Learning Parallelization and Its Application in Spatial Data Mining

In recent years, deep learning has achieved great success in the field of artificial intelligence. The rise of deep learning has accelerated the advent of the intelligent era. However, with the deepening of the layers of deep neural networks and the increasing complexity of algorithm models, the size of the data set used for training is also getting larger and larger, which causes the time required for training to continue to increase, and the parallelization of deep neural networks can effectively solve this problem. Therefore, the research on the parallelization of deep learning becomes more and more important. This article summarizes the current research status of deep learning and its parallelization implementation, and also introduces the related research progress in spatial data processing especially.