Invention Grant
- Patent Title: Deep learning FPGA converter
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Application No.: US15891762Application Date: 2018-02-08
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Publication No.: US11568232B2Publication Date: 2023-01-31
- Inventor: Kuan-Chieh Huang , Yi-Ting Peng
- Applicant: QUANTA COMPUTER INC.
- Applicant Address: TW Taoyuan
- Assignee: QUANTA COMPUTER INC.
- Current Assignee: QUANTA COMPUTER INC.
- Current Assignee Address: TW Taoyuan
- Agency: Nixon Peabody LLP
- Main IPC: G06F9/44
- IPC: G06F9/44 ; G06N3/08 ; G06N3/04 ; G06N3/10 ; G06F30/34 ; G06F9/50 ; H03K19/177

Abstract:
Systems and methods for programming field programmable gate array (FPGA) devices are provided. A trained model for a deep learning process is obtained and converted to design abstraction (DA) code defining logic block circuits for programming an FPGA device. Each of these logic block circuits represents one of a plurality of modules that executes a processing step between different layers of the deep learning process.
Public/Granted literature
- US20190244095A1 DEEP LEARNING FPGA CONVERTER Public/Granted day:2019-08-08
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