ADJUSTMENT OF FPGA SYSTEM DESIGN USING LANGUAGE-BASED MACHINE LEARNING MODELS

    公开(公告)号:US20250013823A1

    公开(公告)日:2025-01-09

    申请号:US18896267

    申请日:2024-09-25

    Abstract: Systems or methods of the present disclosure may provide systems and methods for adjusting a system design for a field-programmable gate array (FPGA) in response to a compilation error based on one or more language-based machine learning (ML) models trained on error messages of prior system designs. A method may include receiving an error message associated with a system design of an FPGA, generating a language-based machine learning (ML) prompt based at least on the error message, and determining an adjustment to the system design based on providing the language-based ML prompt to one or more language-based ML models trained on prior error messages.

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