Patents by Inventor Deepak Vembar

Deepak Vembar 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).

  • Patent number: 12229867
    Abstract: One embodiment provides a graphics processor comprising a block of execution resources, a cache memory, a cache memory prefetcher, and circuitry including a programmable neural network unit, the programmable neural network unit comprising a network hardware block including circuitry to perform neural network operations and activation operations for a layer of a neural network, the programmable neural network unit addressable by cores within the block of graphics cores and the neural network hardware block configured to perform operations associated with a neural network configured to determine a prefetch pattern for the cache memory prefetcher.
    Type: Grant
    Filed: May 1, 2023
    Date of Patent: February 18, 2025
    Assignee: Intel Corporation
    Inventors: Hugues Labbe, Darrel Palke, Sherine Abdelhak, Jill Boyce, Varghese George, Scott Janus, Adam Lake, Zhijun Lei, Zhengmin Li, Mike MacPherson, Carl Marshall, Selvakumar Panneer, Prasoonkumar Surti, Karthik Veeramani, Deepak Vembar, Vallabhajosyula Srinivasa Somayazulu
  • Publication number: 20240323341
    Abstract: A system and method for foveated stereo rendering.
    Type: Application
    Filed: March 25, 2023
    Publication date: September 26, 2024
    Inventors: Oliver GRAU, Deepak VEMBAR
  • Publication number: 20240311962
    Abstract: Described herein are techniques to enhance the user experience for 3D rendered applications via neural frame generation using upsampled optical flow data. In one embodiment, a neural network is trained using both sparse optical flow data and dense optical flow data to enable neural frame generation to be performed by a deployed neural network using only sparse optical flow data. The sparse optical flow data can be upsampled to dense optical flow data by the trained neural network. The neural network can then use the upsampled dense optical flow data to perform frame generation.
    Type: Application
    Filed: April 28, 2023
    Publication date: September 19, 2024
    Applicant: Intel Corporation
    Inventors: Darshan R. Iyer, Deepak Vembar, Changliang Wang, Sumit Bhatia
  • Publication number: 20240303899
    Abstract: Described herein are techniques to enhance the user experience for 3D rendered applications via neural frame generation and neural supersampling. One embodiment provides a latency aware unified neural network for frame interpolation and extrapolation. This unified neural network merges interpolation and extrapolation networks into one generalized network that can be applied to both interpolation and extrapolation, depending on the acceptable latency of performance. A further embodiment provides hardware-efficient and latency-aware spatiotemporal neural frame prediction. Hardware-efficient and latency-aware spatiotemporal neural frame prediction enables both frame generation and machine learning supersampling using a single network, rather than using separate networks for frame generation and supersampling.
    Type: Application
    Filed: March 6, 2023
    Publication date: September 12, 2024
    Applicant: Intel Corporation
    Inventors: Darshan R. Iyer, Deepak Vembar
  • Publication number: 20230360307
    Abstract: One embodiment provides a graphics processor comprising a block of execution resources, a cache memory, a cache memory prefetcher, and circuitry including a programmable neural network unit, the programmable neural network unit comprising a network hardware block including circuitry to perform neural network operations and activation operations for a layer of a neural network, the programmable neural network unit addressable by cores within the block of graphics cores and the neural network hardware block configured to perform operations associated with a neural network configured to determine a prefetch pattern for the cache memory prefetcher.
    Type: Application
    Filed: May 1, 2023
    Publication date: November 9, 2023
    Applicant: Intel Corporation
    Inventors: HUGUES LABBE, DARREL PALKE, SHERINE ABDELHAK, JILL BOYCE, VARGHESE GEORGE, SCOTT JANUS, ADAM LAKE, ZHIJUN LEI, ZHENGMIN LI, MIKE MACPHERSON, CARL MARSHALL, SELVAKUMAR PANNEER, PRASOONKUMAR SURTI, KARTHIK VEERAMANI, DEEPAK VEMBAR, VALLABHAJOSYULA SRINIVASA SOMAYAZULU
  • Patent number: 11790490
    Abstract: An apparatus and method for efficiently improving virtual/real interactions in augmented reality. For example, one embodiment of a method comprises: capturing a raw image including depth data; identifying one or more regions of interest based on a detected spatial proximity of one or more virtual objects and one or more real objects; generating a super-resolution map of the one or more regions of interest using machine-learning techniques or results thereof; detecting interactions between the virtual objects and the real objects using the super-resolution map; and performing one or more graphics processing or general purpose processing operations based on the detected interactions.
    Type: Grant
    Filed: September 28, 2021
    Date of Patent: October 17, 2023
    Assignee: INTEL CORPORATION
    Inventors: Zhengmin Li, Atsuo Kuwahara, Deepak Vembar
  • Patent number: 11676322
    Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.
    Type: Grant
    Filed: October 13, 2021
    Date of Patent: June 13, 2023
    Assignee: Intel Corporation
    Inventors: Hugues Labbe, Darrel Palke, Sherine Abdelhak, Jill Boyce, Varghese George, Scott Janus, Adam Lake, Zhijun Lei, Zhengmin Li, Mike Macpherson, Carl Marshall, Selvakumar Panneer, Prasoonkumar Surti, Karthik Veeramani, Deepak Vembar, Vallabhajosyula Srinivasa Somayazulu
  • Publication number: 20230063678
    Abstract: Methods, systems and apparatuses may provide for technology that detects virtual background content and real-time foreground content associated with a video session, wherein the real-time foreground content depicts a plurality of participants from different physical environments. The technology may also apply a visual correction to one or more of the real-time foreground content or the virtual background content, wherein the visual correction reduces a difference between the real-time foreground content and the virtual background content with respect to one or more lighting parameters and two or more of the plurality of participants. Additionally, the technology may generate a composite result based on the real-time foreground content, the virtual background content, and the visual correction.
    Type: Application
    Filed: September 2, 2021
    Publication date: March 2, 2023
    Inventors: Scott Janus, Deepak Vembar
  • Patent number: 11557085
    Abstract: Embodiments are directed to neural network processing for multi-object three-dimensional (3D) modeling. An embodiment of a computer-readable storage medium includes executable computer program instructions for obtaining data from multiple cameras, the data including multiple images, and generating a 3D model for 3D imaging based at least in part on the data from the cameras, wherein generating the 3D model includes one or more of performing processing with a first neural network to determine temporal direction based at least in part on motion of one or more objects identified in an image of the multiple images or performing processing with a second neural network to determine semantic content information for an image of the multiple images.
    Type: Grant
    Filed: December 4, 2020
    Date of Patent: January 17, 2023
    Assignee: Intel Corporation
    Inventors: Jill Boyce, Soethiha Soe, Selvakumar Panneer, Adam Lake, Nilesh Jain, Deepak Vembar, Glen J. Anderson, Varghese George, Carl Marshall, Scott Janus, Saurabh Tangri, Karthik Veeramani, Prasoonkumar Surti
  • Publication number: 20220392116
    Abstract: A mechanism is described for image frame rendering. An apparatus of embodiments, as described herein, includes one or more processors to receive a plurality of past image frames including a plurality of pixels, receive a predicted optical flow, generate a predicted frame and a confidence map associated with the predicted frame based on the plurality of past image frames and the predicted optical flow, render a first set of the plurality of pixels in the predicted frame based on the confidence map and adding the rendered pixels to the predicted frame to generate a final frame.
    Type: Application
    Filed: June 3, 2021
    Publication date: December 8, 2022
    Applicant: Intel Corporation
    Inventors: Deepak Vembar, Carl S. Marshall
  • Publication number: 20220092741
    Abstract: An apparatus and method for efficiently improving virtual/real interactions in augmented reality. For example, one embodiment of a method comprises: capturing a raw image including depth data; identifying one or more regions of interest based on a detected spatial proximity of one or more virtual objects and one or more real objects; generating a super-resolution map of the one or more regions of interest using machine-learning techniques or results thereof; detecting interactions between the virtual objects and the real objects using the super-resolution map; and performing one or more graphics processing or general purpose processing operations based on the detected interactions.
    Type: Application
    Filed: September 28, 2021
    Publication date: March 24, 2022
    Inventors: Zhengmin LI, Atsuo KUWAHARA, Deepak VEMBAR
  • Publication number: 20220058853
    Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.
    Type: Application
    Filed: October 13, 2021
    Publication date: February 24, 2022
    Applicant: Intel Corporation
    Inventors: HUGUES LABBE, DARREL PALKE, SHERINE ABDELHAK, JILL BOYCE, VARGHESE GEORGE, SCOTT JANUS, ADAM LAKE, ZHIJUN LEI, ZHENGMIN LI, MIKE MACPHERSON, CARL MARSHALL, SELVAKUMAR PANNEER, PRASOONKUMAR SURTI, KARTHIK VEERAMANI, DEEPAK VEMBAR, VALLABHAJOSYULA SRINIVASA SOMAYAZULU
  • Patent number: 11151769
    Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.
    Type: Grant
    Filed: August 9, 2019
    Date of Patent: October 19, 2021
    Assignee: Intel Corporation
    Inventors: Hugues Labbe, Darrel Palke, Sherine Abdelhak, Jill Boyce, Varghese George, Scott Janus, Adam Lake, Zhijun Lei, Zhengmin Li, Mike Macpherson, Carl Marshall, Selvakumar Panneer, Prasoonkumar Surti, Karthik Veeramani, Deepak Vembar, Vallabhajosyula Srinivasa Somayazulu
  • Patent number: 11138692
    Abstract: An apparatus and method for efficiently improving virtual/real interactions in augmented reality. For example, one embodiment of a method comprises: capturing a raw image including depth data; identifying one or more regions of interest based on a detected spatial proximity of one or more virtual objects and one or more real objects; generating a super-resolution map of the one or more regions of interest using machine-learning techniques or results thereof; detecting interactions between the virtual objects and the real objects using the super-resolution map; and performing one or more graphics processing or general purpose processing operations based on the detected interactions.
    Type: Grant
    Filed: November 15, 2019
    Date of Patent: October 5, 2021
    Assignee: INTEL CORPORATION
    Inventors: Zhengmin Li, Atsuo Kuwahara, Deepak Vembar
  • Publication number: 20210090327
    Abstract: Embodiments are directed to neural network processing for multi-object three-dimensional (3D) modeling. An embodiment of a computer-readable storage medium includes executable computer program instructions for obtaining data from multiple cameras, the data including multiple images, and generating a 3D model for 3D imaging based at least in part on the data from the cameras, wherein generating the 3D model includes one or more of performing processing with a first neural network to determine temporal direction based at least in part on motion of one or more objects identified in an image of the multiple images or performing processing with a second neural network to determine semantic content information for an image of the multiple images.
    Type: Application
    Filed: December 4, 2020
    Publication date: March 25, 2021
    Applicant: Intel Corporation
    Inventors: Jill Boyce, Soethiha Soe, Selvakamur Panneer, Adam Lake, Nilesh Jain, Deepak Vembar, Glen J. Anderson, Varghese George, Carl Marshall, Scott Janus, Saurabh Tangri, Karthik Veeramani, Prasoonkumar Surti
  • Patent number: 10861225
    Abstract: Embodiments are directed to neural network processing for multi-object three-dimensional (3D) modeling. An embodiment of a computer-readable storage medium includes executable computer program instructions for obtaining data from multiple cameras, the data including multiple images, and generating a 3D model for 3D imaging based at least in part on the data from the cameras, wherein generating the 3D model includes one or more of performing processing with a first neural network to determine temporal direction based at least in part on motion of one or more objects identified in an image of the multiple images or performing processing with a second neural network to determine semantic content information for an image of the multiple images.
    Type: Grant
    Filed: December 27, 2018
    Date of Patent: December 8, 2020
    Assignee: INTEL CORPORATION
    Inventors: Jill Boyce, Soethiha Soe, Selvakumar Panneer, Adam Lake, Nilesh Jain, Deepak Vembar, Glen J. Anderson, Varghese George, Carl Marshall, Scott Janus, Saurabh Tangri, Karthik Veeramani, Prasoonkumar Surti
  • Patent number: 10712834
    Abstract: Embodiments for providing a wearable device are generally described herein. A wearable device may include a processor having memory and communicatively coupled to a plurality of display areas; and an orientation sensing module communicatively coupled to the processor to determine at least one of an orientation and a location of at least one of the plurality of display areas with respect to a point of view of a user; wherein the processor provides a function for at least one of the plurality of display areas based on the determined at least one of the orientation and the location of at least one of the plurality of display areas by the orientation sensing module.
    Type: Grant
    Filed: August 28, 2017
    Date of Patent: July 14, 2020
    Assignee: INTEL CORPORATION
    Inventors: Giuseppe Raffa, Deepak Vembar, Glen J. Anderson, Ryan Scott Brotman, Jamie Sherman, Francisco Javier Fernandez
  • Publication number: 20200184602
    Abstract: An apparatus and method for efficiently improving virtual/real interactions in augmented reality. For example, one embodiment of a method comprises: capturing a raw image including depth data; identifying one or more regions of interest based on a detected spatial proximity of one or more virtual objects and one or more real objects; generating a super-resolution map of the one or more regions of interest using machine-learning techniques or results thereof; detecting interactions between the virtual objects and the real objects using the super-resolution map; and performing one or more graphics processing or general purpose processing operations based on the detected interactions.
    Type: Application
    Filed: November 15, 2019
    Publication date: June 11, 2020
    Inventors: Zhengmin LI, Atsuo KUWAHARA, Deepak VEMBAR
  • Publication number: 20200051309
    Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.
    Type: Application
    Filed: August 9, 2019
    Publication date: February 13, 2020
    Applicant: Intel Corporation
    Inventors: HUGUES LABBE, DARREL PALKE, SHERINE ABDELHAK, JILL BOYCE, VARGHESE GEORGE, SCOTT JANUS, ADAM LAKE, ZHIJUN LEI, ZHENGMIN LI, MIKE MACPHERSON, CARL MARSHALL, SELVAKUMAR PANNEER, PRASOONKUMAR SURTI, KARTHIK VEERAMANI, DEEPAK VEMBAR, VALLABHAJOSYULA SRINIVASA SOMAYAZULU
  • Publication number: 20190362461
    Abstract: Embodiments described herein provide a method comprises constructing an application tool profile from a history of tools used by an application to create one or more documents, storing the application tool profile in a memory; and creating a customized application toolset for the application using the application tool profile. Other embodiments may be described and claimed.
    Type: Application
    Filed: August 9, 2019
    Publication date: November 28, 2019
    Applicant: Intel Corporation
    Inventors: VARGHESE GEORGE, JILL BOYCE, SELVAKUMAR PANNEER, DEEPAK VEMBAR, KARTHIK VEERAMANI, PRASOONKUMAR SURTI, SCOTT JANUS, SOETHIHA SOE, NILESH JAIN, SAURABH TANGRI, GLEN J. ANDERSON, ADAM LAKE, CARL MARSHALL