Invention Grant
- Patent Title: System and method for adapting a neural network model on a hardware platform
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Application No.: US16728884Application Date: 2019-12-27
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Publication No.: US11610117B2Publication Date: 2023-03-21
- Inventor: Michael Driscoll
- Applicant: Tesla, Inc.
- Applicant Address: US TX Austin
- Assignee: Tesla, Inc.
- Current Assignee: Tesla, Inc.
- Current Assignee Address: US TX Austin
- Agency: Knobbe, Martens, Olson & Bear, LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F17/16 ; G06K9/62

Abstract:
Systems and methods for adapting a neural network model on a hardware platform. An example method includes obtaining neural network model information comprising decision points associated with a neural network, with one or more first decision points being associated with a layout of the neural network. Platform information associated with a hardware platform for which the neural network model information is to be adapted is accessed. Constraints associated with adapting the neural network model information to the hardware platform are determined based on the platform information, with a first constraint being associated with a processing resource of the hardware platform and with a second constraint being associated with a performance metric. A candidate configuration for the neural network is generated via execution of a satisfiability solver based on the constraints, with the candidate configuration assigns values to the plurality of decision points.
Public/Granted literature
- US20200210832A1 SYSTEM AND METHOD FOR ADAPTING A NEURAL NETWORK MODEL ON A HARDWARE PLATFORM Public/Granted day:2020-07-02
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