Satellite Remote Sensing Application Model Parallel Training Technology Research

In response to the long training time of satellite remote sensing application models, this paper first introduces the main methods of parallel training, as well as the support provided by PyTorch for parallel training. Based on this, the target detection model YOLOv4 and the U-Net-based land-sea segmentation model were trained in parallel, and the experiments showed that the training time of both types of models was significantly reduced.