Patents by Inventor Tobias Joseph Kastulus Edler von Koch

Tobias Joseph Kastulus Edler von Koch 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: 11809981
    Abstract: A method of generating executable instructions for a computing system is provided. The method comprises: receiving a first set of instructions including a kernel of a first operator and a kernel of a second operator, the kernel of the first operator including instructions of the first operator and write instructions to a virtual data node, the kernel of the second operator including instructions of the second operator and read instructions to the virtual data node; determining, based on a mapping between the write instructions and read instructions, instructions of data transfer operations between the first operator and the second operator; and generating a second set of instructions representing a fused operator of the first operator and the second operator, the second set of instructions including the instructions of the first operator, the instructions of the second operator, and the instructions of the data transfer operations.
    Type: Grant
    Filed: November 27, 2019
    Date of Patent: November 7, 2023
    Assignee: Amazon Technologies, Inc.
    Inventors: Animesh Jain, Tobias Joseph Kastulus Edler von Koch, Yizhi Liu, Taemin Kim, Jindrich Zejda, Yida Wang, Vinod Sharma, Richard John Heaton, Randy Renfu Huang
  • Patent number: 11144291
    Abstract: Methods of accelerating the execution of neural networks are disclosed. A description of a neural network may be received. A plurality of operators may be identified based on the description of the neural network. A plurality of symbolic models associated with the plurality of operators may be generated. For each symbolic model, a nested loop associated with an operator may be identified, a loop order may be defined, and a set of data dependencies may be defined. A set of inter-operator dependencies may be extracted based on the description of the neural network. The plurality of symbolic models and the set of inter-operator dependencies may be analyzed to identify a combinable pair of nested loops. The combinable pair of nested loops may be combined to form a combined nested loop.
    Type: Grant
    Filed: November 27, 2019
    Date of Patent: October 12, 2021
    Assignee: Amazon Technologies, Inc.
    Inventors: Hongbin Zheng, Preston Pengra Briggs, Tobias Joseph Kastulus Edler von Koch, Taemin Kim, Randy Renfu Huang
  • Patent number: 11003429
    Abstract: Scheduling of the operations of an integrated circuit device such as a hardware accelerator, including scheduling of movement of data into and out of the accelerator, can be performed by a compiler that produces program code for the accelerator. The compiler can produce a graph that represents operations to be performed by the accelerator. Using the graph, the compiler can determine estimated execution times for the operations represented by each node in the graph. The compiler can schedule operations by determining an estimated execution time for set of dependent operations that depend from an operation. The compiler can then select an operation that has a shortest estimated execution time from among a set of operations and which has a set of dependent operations that has a longest estimated execution time as compared to other sets of dependent operations.
    Type: Grant
    Filed: February 4, 2019
    Date of Patent: May 11, 2021
    Assignee: Amazon Technologies, Inc.
    Inventors: Jindrich Zejda, Jeffrey T. Huynh, Tobias Joseph Kastulus Edler von Koch, Drazen Borkovic, Taemin Kim