Patents by Inventor Paul Martin Springer

Paul Martin Springer 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).

  • APPLICATION PROGRAMMING INTERFACE TO ALLOCATE MEMORY TO PERFORM TENSOR OPERATIONS
    Publication number: 20250156683
    Abstract: Apparatuses, systems, and techniques to perform one or more operations using a tensor. In at least one embodiment, one or more circuits are to perform an application programming interface (API) to perform one or more operations using one or more tensors based on at least one or more indications of the plurality of operations by the API, one or more compiler options indicated by the API, and/or one of one or more indications of an amount of storage to be used to perform the one or more operations.
    Type: Application
    Filed: November 15, 2023
    Publication date: May 15, 2025
    Inventors: Paul Martin Springer, Markus Hoehnerbach, Christos Psarras, Ali Mohamad Charara, Adam Jedrych, Yao-Lung Fang, Satya Narayan Varadhan
  • APPLICATION PROGRAMMING INTERFACE TO PROVIDE COMPILER OPTIONS TO PERFORM TENSOR OPERATIONS
    Publication number: 20250156205
    Abstract: Apparatuses, systems, and techniques to perform one or more operations using a tensor. In at least one embodiment, one or more circuits are to perform an application programming interface (API) to perform one or more operations using one or more tensors based on at least one or more indications of the plurality of operations by the API, one or more compiler options indicated by the API, and/or one of one or more indications of an amount of storage to be used to perform the one or more operations.
    Type: Application
    Filed: November 15, 2023
    Publication date: May 15, 2025
    Inventors: Paul Martin Springer, Markus Hoehnerbach, Christos Psarras, Ali Mohamad Charara, Adam Jedrych, Yao-Lung Fang, Satya Narayan Varadhan
  • APPLICATION PROGRAMMING INTERFACE TO PERFORM TENSOR OPERATIONS
    Publication number: 20250156984
    Abstract: Apparatuses, systems, and techniques to perform one or more operations using a tensor. In at least one embodiment, one or more circuits are to perform an application programming interface (API) to perform one or more operations using one or more tensors based on at least one or more indications of the plurality of operations by the API, one or more compiler options indicated by the API, and/or one of one or more indications of an amount of storage to be used to perform the one or more operations.
    Type: Application
    Filed: November 15, 2023
    Publication date: May 15, 2025
    Inventors: Paul Martin Springer, Markus Hoehnerbach, Christos Psarras, Ali Mohamad Charara, Adam Jedrych, Yao-Lung Fang, Satya Narayan Varadhan
  • TENSOR DIMENSION ORDERING TECHNIQUES
    Publication number: 20240338175
    Abstract: Apparatuses, systems, and techniques to store tensor operands. In at least one embodiment, modes of one or more tensor operands are sorted based, at least in part, on one or more performance metrics of one or more tensor operations to be performed using said one or more tensor operands.
    Type: Application
    Filed: May 1, 2023
    Publication date: October 10, 2024
    Inventors: Paul Martin Springer, Ali Mohamad Charara, Markus Hoehnerbach, Andreas Roland Hehn
  • SCALABLE TENSOR NETWORK CONTRACTION USING REINFORCEMENT LEARNING
    Publication number: 20230229916
    Abstract: A method for contracting a tensor network is provided. The method comprises generating a graph representation of the tensor network, processing the graph representation to determine a contraction for the tensor network by an agent that implements a reinforcement learning algorithm, and processing the tensor network in accordance with the contraction to generate a contracted tensor network.
    Type: Application
    Filed: January 20, 2023
    Publication date: July 20, 2023
    Inventors: Gal Chechik, Eli Alexander Meirom, Haggai Maron, Brucek Kurdo Khailany, Paul Martin Springer, Shie Mannor
  • Selecting computational kernel variants using neural networks
    Patent number: 11625605
    Abstract: Apparatuses, systems, and techniques to optimize kernel selection for performing a computation. In at least one embodiment, a neural network is trained and utilized to generate a list of kernels so that an (e.g., optimal) kernel may be identified. The neural network receives characteristics of the input matrices and determines relevancy scores for a list of possible kernels. Based on an ordered listing of kernels by relevant score, a kernel is selected from the list and utilized to perform the computation and provide the result.
    Type: Grant
    Filed: December 20, 2019
    Date of Patent: April 11, 2023
    Assignee: Nvidia Corporation
    Inventors: Jonathan Edward Barker, Christopher Thomas Cheng, Paul Martin Springer, Wojciech Jablonski
  • SELECTING COMPUTATIONAL KERNEL VARIANTS USING NEURAL NETWORKS
    Publication number: 20210192334
    Abstract: Apparatuses, systems, and techniques to optimize kernel selection for performing a computation. In at least one embodiment, a neural network is trained and utilized to generate a list of kernels so that an (e.g., optimal) kernel may be identified. The neural network receives characteristics of the input matrices and determines relevancy scores for a list of possible kernels. Based on an ordered listing of kernels by relevant score, a kernel is selected from the list and utilized to perform the computation and provide the result.
    Type: Application
    Filed: December 20, 2019
    Publication date: June 24, 2021
    Inventors: Jonathan Edward BARKER, Christopher Thomas CHENG, Paul Martin SPRINGER, Wojciech JABLONSKI
  • PROCESSOR AND SYSTEM TO CONVERT TENSOR OPERATIONS IN MACHINE LEARNING
    Publication number: 20210064987
    Abstract: Apparatuses, systems, and techniques to convert between tensor convolution and tensor contraction operations. In at least one embodiment, one or more convolution operations are performed on image data by at least contracting one or more tensors to generate one or more feature maps.
    Type: Application
    Filed: September 3, 2019
    Publication date: March 4, 2021
    Inventors: Paul Martin Springer, Chenhan Yu