Patents by Inventor Rengjing Zhang

Rengjing Zhang 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).

  • Machine learning-based parasitic extraction automation for circuit design and verification
    Patent number: 10796046
    Abstract: This application discloses a computing system implementing a parasitic extraction tool to generate parasitic netlists from tests cases including test layout models of integrated circuit structures. The test cases include reference netlists corresponding to intended parasitic netlists for the test layout models. The computing system can determine values for scaling coefficients that, when utilized by the parasitic extraction tool to generate the parasitic netlists, allow differences between the parasitic netlists and the reference netlists to fall below threshold levels. The determination of the scaling coefficients is performed by iteratively adjusting the values of the scaling coefficients based on differences between the reference netlists and the parasitic netlists generated with the scaling coefficients having the adjusted values.
    Type: Grant
    Filed: August 23, 2019
    Date of Patent: October 6, 2020
    Assignee: Mentor Graphics Corporation
    Inventors: Vasileios Kourkoulos, Rengjing Zhang, Joshua Adkins
  • MACHINE LEARNING-BASED PARASITIC EXTRACTION AUTOMATION FOR CIRCUIT DESIGN AND VERIFICATION
    Publication number: 20200233931
    Abstract: This application discloses a computing system implementing a parasitic extraction tool to generate parasitic netlists from tests cases including test layout models of integrated circuit structures. The test cases include reference netlists corresponding to intended parasitic netlists for the test layout models. The computing system can determine values for scaling coefficients that, when utilized by the parasitic extraction tool to generate the parasitic netlists, allow differences between the parasitic netlists and the reference netlists to fall below threshold levels. The determination of the scaling coefficients is performed by iteratively adjusting the values of the scaling coefficients based on differences between the reference netlists and the parasitic netlists generated with the scaling coefficients having the adjusted values.
    Type: Application
    Filed: August 23, 2019
    Publication date: July 23, 2020
    Inventors: Vasileios Kourkoulos, Rengjing Zhang, Joshua Adkins