Implementation method for parallel acceleration of ResNet based on general neural network processor

The invention discloses an implementation method for parallel acceleration of ResNet based on a general neural network processor. The method comprises the following steps: loading a data set and a weight into a register from a central cache region, carrying out the operation of a convolutional layer, and loading a weight matrix into a matrix multiplication unit from the register; sending the data set matrix to a matrix multiplication unit in a streaming data mode, writing an operation result back to a register, and repeating the process until all data are processed; using a vector compression unit to complete batch standardization operation; completing the operation of linear rectification by using an SIMD operation unit ; completing the operation of a pooling layer by using the SIMD operation unit and a vector compression unit; completing operation of a full connection layer by using a matrix multiplication unit, and writing a result back to the register; and writing the result in the register back to the ce