Patents by Inventor Dan Luu

Dan Luu 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: 20230206070
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Application
    Filed: March 1, 2023
    Publication date: June 29, 2023
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Patent number: 11620508
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Grant
    Filed: January 11, 2019
    Date of Patent: April 4, 2023
    Assignee: Google LLC
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Patent number: 11586920
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: June 29, 2020
    Date of Patent: February 21, 2023
    Assignee: Google LLC
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20220366255
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: July 27, 2022
    Publication date: November 17, 2022
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Patent number: 11049016
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: March 19, 2020
    Date of Patent: June 29, 2021
    Assignee: Google LLC
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20210019618
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: June 29, 2020
    Publication date: January 21, 2021
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20200218981
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: March 19, 2020
    Publication date: July 9, 2020
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Patent number: 10699188
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: August 25, 2017
    Date of Patent: June 30, 2020
    Assignee: Google LLC
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20200057942
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: October 25, 2019
    Publication date: February 20, 2020
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20190354862
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: August 1, 2019
    Publication date: November 21, 2019
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20190228301
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Application
    Filed: January 11, 2019
    Publication date: July 25, 2019
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Patent number: 10192162
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Grant
    Filed: September 3, 2015
    Date of Patent: January 29, 2019
    Assignee: Google LLC
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Patent number: 10074051
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Grant
    Filed: December 22, 2016
    Date of Patent: September 11, 2018
    Assignee: Google LLC
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Publication number: 20180046907
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: August 25, 2017
    Publication date: February 15, 2018
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Patent number: 9747546
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: September 3, 2015
    Date of Patent: August 29, 2017
    Assignee: Google Inc.
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Patent number: 9710748
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: December 22, 2016
    Date of Patent: July 18, 2017
    Assignee: Google Inc.
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20170103315
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Application
    Filed: December 22, 2016
    Publication date: April 13, 2017
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Publication number: 20170103313
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: December 22, 2016
    Publication date: April 13, 2017
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu
  • Publication number: 20160342889
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of layers, the circuit comprising: activation circuitry configured to receive a vector of accumulated values and configured to apply a function to each accumulated value to generate a vector of activation values; and normalization circuitry coupled to the activation circuitry and configured to generate a respective normalized value from each activation value.
    Type: Application
    Filed: September 3, 2015
    Publication date: November 24, 2016
    Applicant: Google Inc.
    Inventors: Gregory Michael Thorson, Christopher Aaron Clark, Dan Luu
  • Publication number: 20160342891
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Application
    Filed: September 3, 2015
    Publication date: November 24, 2016
    Applicant: Google Inc.
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu