Patents by Inventor Matthew R. Fojtik

Matthew R. Fojtik 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).

  • Scalable multi-die deep learning system
    Patent number: 11769040
    Abstract: A distributed deep neural net (DNN) utilizing a distributed, tile-based architecture implemented on a semiconductor package. The package includes multiple chips, each with a central processing element, a global memory buffer, and processing elements. Each processing element includes a weight buffer, an activation buffer, and multiply-accumulate units to combine, in parallel, the weight values and the activation values.
    Type: Grant
    Filed: July 19, 2019
    Date of Patent: September 26, 2023
    Assignee: NVIDIA CORP.
    Inventors: Yakun Shao, Rangharajan Venkatesan, Nan Jiang, Brian Matthew Zimmer, Jason Clemons, Nathaniel Pinckney, Matthew R Fojtik, William James Dally, Joel S. Emer, Stephen W. Keckler, Brucek Khailany
  • SCALABLE MULTI-DIE DEEP LEARNING SYSTEM
    Publication number: 20200082246
    Abstract: A distributed deep neural net (DNN) utilizing a distributed, tile-based architecture implemented on a semiconductor package. The package includes multiple chips, each with a central processing element, a global memory buffer, and processing elements. Each processing element includes a weight buffer, an activation buffer, and multiply-accumulate units to combine, in parallel, the weight values and the activation values.
    Type: Application
    Filed: July 19, 2019
    Publication date: March 12, 2020
    Applicant: NVIDIA Corp.
    Inventors: Yakun Shao, Rangharajan Venkatesan, Nan Jiang, Brian Matthew Zimmer, Jason Clemons, Nathaniel Pinckney, Matthew R. Fojtik, William James Dally, Joel S. Emer, Stephen W. Keckler, Brucek Khailany