Patents by Inventor PRATAP JOSEPH CHANDAR

PRATAP JOSEPH CHANDAR 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).

  • Sample driven profile guided optimization with precise correlation
    Patent number: 11003428
    Abstract: A profile guided optimization compiler utilizes sample profile data including a control flow representation of a program having block counts associated with each basic block of the program, and edge counts associated with each control flow edge estimated from the block counts. The sample profile data utilizes correlation data to map the address of a sampled instruction from a fully optimized binary directly into a corresponding basic block of source code control flow of the program using a relative virtual address (RVA) that is associated with each source code basic block and the sampled instruction. The correlation data is able to differentiate multiple blocks on the same source code line and handle inlining and optimizations with greater precision and efficiency. The block counts are then used to guide the optimization of the program.
    Type: Grant
    Filed: May 25, 2016
    Date of Patent: May 11, 2021
    Assignee: MICROSOFT TECHNOLGY LICENSING, LLC.
    Inventors: Wenlei He, Ten Tzen, Pratap Joseph Chandar
  • SAMPLE DRIVEN PROFILE GUIDED OPTIMIZATION WITH PRECISE CORRELATION
    Publication number: 20170344349
    Abstract: A profile guided optimization compiler utilizes sample profile data including a control flow representation of a program having block counts associated with each basic block of the program, and edge counts associated with each control flow edge estimated from the block counts. The sample profile data utilizes correlation data to map the address of a sampled instruction from a fully optimized binary directly into a corresponding basic block of source code control flow of the program using a relative virtual address (RVA) that is associated with each source code basic block and the sampled instruction. The correlation data is able to differentiate multiple blocks on the same source code line and handle inlining and optimizations with greater precision and efficiency. The block counts are then used to guide the optimization of the program.
    Type: Application
    Filed: May 25, 2016
    Publication date: November 30, 2017
    Inventors: WENLEI HE, TEN TZEN, PRATAP JOSEPH CHANDAR