anupam-io/ES203-COA-CNN
ES-203 Computer Organization & Architecture CNN on FPGA board
This project helps computer organization and architecture students and hardware designers implement Convolutional Neural Networks (CNNs) directly on FPGA boards. It takes C-style CNN algorithms and provides methods to convert them into efficient Verilog `always` blocks for hardware synthesis. The output is a working CNN design optimized for FPGA hardware, used by students and engineers working with digital logic and embedded systems.
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Use this if you are a student or hardware engineer looking to implement machine learning models, specifically CNNs, onto FPGA hardware efficiently.
Not ideal if you are looking for a high-level software library or framework for machine learning, as this focuses on low-level hardware implementation.
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17
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8
Language
Verilog
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Last pushed
Feb 23, 2022
Commits (30d)
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