Study on Pruning Optimization Technology Based on Deep Learning
This paper describes the optimization methods of existing convolutional neural network models.Based on hardware conditions,explore the reasons,main optimization methods,and general process for proposing four optimization methods:low rank decomposition,knowledge distillation,quantization,and pruning.It analyzes the evolution process of low rank decomposition and knowledge distillation,introduces specific optimization methods for quantization and pruning,and the relevant basic knowledge involved.After comparison and summary,it has been concluded that there are two deep learning optimization methods,quantification and pruning,which are more widely used for controlling software costs,applying in various fields,and connecting with hardware.
deep learninglow rank decompositionknowledge distillationquantization and pruning
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