Patents by Inventor Ruidong YAN

Ruidong YAN 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: 20250077308
    Abstract: The present disclosure relates to the field of data processing. Provided is a distributed computing method, comprising: acquiring a data computing task; splitting the data computing task to obtain subtasks, deploying the subtasks to computing nodes, and configuring a parallel mode for each of the computing nodes in a distributed training universal frame; configuring a connection manner and a communication synchronization manner between the computing nodes; optimizing information synchronization efficiency for the computing nodes by using a gradient optimization algorithm or a non-gradient optimization algorithm; and aggregating intermediate results generated by the computing nodes, and outputting a corresponding final computing result.
    Type: Application
    Filed: September 29, 2022
    Publication date: March 6, 2025
    Applicant: SUZHOU METABRAIN INTELLIGENT TECHNOLOGY CO., LTD.
    Inventors: Ruidong YAN, Lu LIU, Liang JIN, Cong XU
  • Publication number: 20250068929
    Abstract: The embodiments of the present disclosure relate to the technical field of computers. Disclosed are a method and apparatus for information fusion, a method and apparatus for data communication, and an electronic device and a non-transitory computer-readable storage medium. The method for information fusion includes: in response to that a communication triggering condition is met, acquiring a local parameter of each of workers in a distributed training system, where the communication triggering condition is that all key nodes complete tasks of the current round of training; selecting N key nodes participating in the next round of training, and fusing local parameters of the N key nodes to obtain a global parameter; and sending the global parameter to each of the workers, and sending a training command to the key nodes to the key nodes execute tasks of next round of training based on the global parameter.
    Type: Application
    Filed: November 23, 2023
    Publication date: February 27, 2025
    Applicant: IEIT SYSTEMS CO., LTD.
    Inventors: Ruidong YAN, Zhenhua GUO, Yaqian ZHAO, Zhiyong QIU
  • Publication number: 20250069280
    Abstract: An image generating method and apparatus, and a device and a medium are disclosed. The method comprises: acquiring weakly correlated image-text data pairs, and creating an image-text data set according to the weakly correlated image-text data pairs, wherein the weakly correlated image-text data pairs are image-text data pairs in which images and texts have weak correlations (S11); training, by using the image-text data set, an image generation model which is preconstructed on the basis of an adversarial network, so as to obtain a trained image generation model, wherein the image generation model includes a generator for generating an image, and a discriminator for identifying the authenticity of the image and calculating a corresponding loss value (S12); and after when text data to be processed has been acquired, generating, by using the trained image generation model, an image corresponding to the said text data (S13).
    Type: Application
    Filed: September 28, 2022
    Publication date: February 27, 2025
    Inventors: Yaqian ZHAO, Lu LIU, Rengang LI, Zhenhua GUO, Ruidong YAN, Cong XU, Liang JIN
  • Publication number: 20240311193
    Abstract: A method and apparatus for allocating a computing task of a neural network in heterogeneous resources, a computer device, and a storage medium. The method includes: acquiring task information of the computing task of the neural network and resource information of the heterogeneous resources; determining, according to the task information and the resource information, an allocation mode for allocating each subtask to the heterogeneous resources for execution and a task processing cost corresponding to each allocation mode; constructing a directed acyclic graph according to each allocation mode and each task processing cost; obtaining a value of a loss function corresponding to each allocation path according to the task processing cost corresponding to each subtask in an allocation path of the directed acyclic graph; and selecting a target allocation path according to the value of each loss function.
    Type: Application
    Filed: April 28, 2022
    Publication date: September 19, 2024
    Inventors: Rengang LI, Lu LIU, Yaqian ZHAO, Zhenhua GUO, Ruidong YAN, Cong XU, Liang JIN