Patents by Inventor Benoit Steiner

Benoit Steiner 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).

  • DEVICE PLACEMENT OPTIMIZATION WITH REINFORCEMENT LEARNING
    Publication number: 20240062062
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.
    Type: Application
    Filed: October 3, 2023
    Publication date: February 22, 2024
    Inventors: Samuel Bengio, Mohammad Norouzi, Benoit Steiner, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le, Naveen Kumar, Yuefeng Zhou, Rasmus Munk Larsen
  • Device placement optimization with reinforcement learning
    Patent number: 11803747
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.
    Type: Grant
    Filed: May 20, 2020
    Date of Patent: October 31, 2023
    Assignee: Google LLC
    Inventors: Samuel Bengio, Mohammad Norouzi, Benoit Steiner, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le, Naveen Kumar, Yuefeng Zhou, Rasmus Munk Larsen
  • Hierarchical device placement with reinforcement learning
    Patent number: 11455514
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices includes receiving data specifying machine learning operations, and determining a placement that assigns each of the operations specified by the data to a respective device from the multiple hardware devices.
    Type: Grant
    Filed: August 28, 2019
    Date of Patent: September 27, 2022
    Assignee: Google LLC
    Inventors: Benoit Steiner, Anna Darling Goldie, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le
  • DEVICE PLACEMENT OPTIMIZATION WITH REINFORCEMENT LEARNING
    Publication number: 20200279163
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.
    Type: Application
    Filed: May 20, 2020
    Publication date: September 3, 2020
    Inventors: Samuel Bengio, Mohammad Norouzi, Benoit Steiner, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le, Naveen Kumar, Yuefeng Zhou, Rasmus Munk Larsen
  • Device placement optimization with reinforcement learning
    Patent number: 10692003
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.
    Type: Grant
    Filed: June 19, 2019
    Date of Patent: June 23, 2020
    Assignee: Google LLC
    Inventors: Samuel Bengio, Mohammad Norouzi, Benoit Steiner, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le, Naveen Kumar, Yuefeng Zhou, Rasmus Munk Larsen
  • HIERARCHICAL DEVICE PLACEMENT WITH REINFORCEMENT LEARNING
    Publication number: 20190392294
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices includes receiving data specifying machine learning operations, and determining a placement that assigns each of the operations specified by the data to a respective device from the multiple hardware devices.
    Type: Application
    Filed: August 28, 2019
    Publication date: December 26, 2019
    Inventors: Benoit Steiner, Anna Darling Goldie, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le
  • Hierarchical device placement with reinforcement learning
    Patent number: 10438113
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices includes receiving data specifying machine learning operations, and determining a placement that assigns each of the operations specified by the data to a respective device from the multiple hardware devices.
    Type: Grant
    Filed: July 19, 2018
    Date of Patent: October 8, 2019
    Assignee: Google LLC
    Inventors: Benoit Steiner, Anna Darling Goldie, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le
  • DEVICE PLACEMENT OPTIMIZATION WITH REINFORCEMENT LEARNING
    Publication number: 20190303761
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.
    Type: Application
    Filed: June 19, 2019
    Publication date: October 3, 2019
    Inventors: Samy Bengio, Mohammad Edward Norouzi, Benoit Steiner, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le, Naveen Kumar, Yuefeng Zhou, Rasmus Munk Larsen
  • HIERARCHICAL DEVICE PLACEMENT WITH REINFORCEMENT LEARNING
    Publication number: 20190026624
    Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices includes receiving data specifying machine learning operations, and determining a placement that assigns each of the operations specified by the data to a respective device from the multiple hardware devices.
    Type: Application
    Filed: July 19, 2018
    Publication date: January 24, 2019
    Inventors: Benoit Steiner, Anna Darling Goldie, Jeffrey Adgate Dean, Hieu Hy Pham, Azalia Mirhoseini, Quoc V. Le
  • Optimized matrix multiplication using vector multiplication of interleaved matrix values
    Patent number: 10073817
    Abstract: The present disclosure relates to optimized matrix multiplication using vector multiplication of interleaved matrix values. Two matrices to be multiplied are organized into specially ordered vectors, which are multiplied together to produce a portion of a product matrix.
    Type: Grant
    Filed: October 24, 2017
    Date of Patent: September 11, 2018
    Assignee: Google LLC
    Inventors: Nishant Patil, Matthew Sarett, Rama Krishna Govindaraju, Benoit Steiner, Vincent O. Vanhoucke
  • Optimized matrix multiplication using vector multiplication of interleaved matrix values
    Patent number: 9830303
    Abstract: The present disclosure relates to optimized matrix multiplication using vector multiplication of interleaved matrix values. Two matrices to be multiplied are organized into specially ordered vectors, which are multiplied together to produce a portion of a product matrix.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: November 28, 2017
    Assignee: Google Inc.
    Inventors: Nishant Patil, Matthew Sarett, Rama Krishna Govindaraju, Benoit Steiner, Vincent O. Vanhoucke
  • Optimized matrix multiplication using vector multiplication of interleaved matrix values
    Patent number: 9645974
    Abstract: The present disclosure relates to optimized matrix multiplication using vector multiplication of interleaved matrix values. Two matrices to be multiplied are organized into specially ordered vectors, which are multiplied together to produce a portion of a product matrix.
    Type: Grant
    Filed: March 11, 2015
    Date of Patent: May 9, 2017
    Assignee: Google Inc.
    Inventors: Nishant Patil, Matthew Sarett, Rama Krishna Govindaraju, Benoit Steiner, Vincent O. Vanhoucke