Patents by Inventor Shilpa Rajagopalan

Shilpa Rajagopalan 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).

  • Real-time low latency computer vision/machine learning compute accelerator with smart convolutional neural network scheduler
    Patent number: 11816871
    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: Grant
    Filed: December 30, 2020
    Date of Patent: November 14, 2023
    Assignees: 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
  • REAL-TIME LOW LATENCY COMPUTER VISION/MACHINE LEARNING COMPUTE ACCELERATOR WITH SMART CONVOLUTIONAL NEURAL NETWORK SCHEDULER
    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