Patents by Inventor David Porpino Sobreira Marques

David Porpino Sobreira Marques 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: 20220207783
    Abstract: Methods and devices are provided for processing image data on a sub-frame portion basis using layers of a convolutional neural network. The processing device comprises memory and a processor. The processor is configured to receive frames of image data comprising sub-frame portions, schedule a first sub-frame portion of a first frame to be processed by a first layer of the convolutional neural network when the first sub-frame portion is available for processing, process the first sub-frame portion by the first layer and continue the processing of the first sub-frame portion by the first layer when it is determined that there is sufficient image data available for the first layer to continue processing of the first sub-frame portion. Processing on a sub-frame portion basis continues for subsequent layers such that processing by a layer can begin as soon as sufficient data is available for the layer.
    Type: Application
    Filed: December 30, 2020
    Publication date: June 30, 2022
    Applicants: Advanced Micro Devices, Inc., ATI Technologies ULC
    Inventors: Tung Chuen Kwong, David Porpino Sobreira Marques, King Chiu Tam, Shilpa Rajagopalan, Benjamin Koon Pan Chan, Vickie Youmin Wu
  • Publication number: 20200380383
    Abstract: Systems, apparatuses, and methods for implementing a safety monitor framework for a safety-critical inference application are disclosed. A system includes a safety-critical inference application, a safety monitor, and an inference accelerator engine. The safety monitor receives an input image, test data, and a neural network specification from the safety-critical inference application. The safety monitor generates a modified image by adding additional objects outside of the input image. The safety monitor provides the modified image and neural network specification to the inference accelerator engine which processes the modified image and provides outputs to the safety monitor. The safety monitor determines the likelihood of erroneous processing of the original input image by comparing the outputs for the additional objects with a known good result. The safety monitor complements the overall fault coverage of the inference accelerator engine and covers faults only observable at the network level.
    Type: Application
    Filed: May 28, 2019
    Publication date: December 3, 2020
    Inventors: Tung Chuen Kwong, Benjamin Koon Pan Chan, David Porpino Sobreira Marques, Clarence Ip, Hung Wilson Yu