Patents by Inventor Chuliang GUO

Chuliang GUO has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220207374
    Abstract: Disclosed in the present invention is a mixed-granularity-based joint sparse method for a neural network. The joint sparse method comprises independent vector-wise fine-grained sparsity and block-wise coarse-grained sparsity; and a final pruning mask is obtained by performing a bitwise logic AND operation on pruning masks independently generated by two sparse methods, and then a weight matrix of the neural network after sparsity is obtained. The joint sparsity of the present invention always obtains the reasoning speed between a block sparsity mode and a balanced sparsity mode without considering the vector row size of the vector-wise fine-grained sparsity and the vector block size of the block-wise coarse-grained sparsity. Pruning for a convolutional layer and a fully-connected layer of a neural network has the advantages of variable sparse granularity, acceleration of general hardware reasoning and high accuracy of model reasoning.
    Type: Application
    Filed: November 2, 2021
    Publication date: June 30, 2022
    Applicant: ZHEJIANG UNIVERSITY
    Inventors: Cheng ZHUO, Chuliang GUO, Xunzhao YIN