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Light-weighted neural network inference for object detection on small-scale FPGA board

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iSmartDNN

This is a repository for FPGA-based neural network inference of iSmart2 team of Design Automation Conference 2018 (https://www.dac.com/content/2018-system-design-contest). iSmart2 teammembers are from UIUC, the Boeing company, IBM and Inspirit Iot.

Repo organization

DNN_train: The DNN model definition and training scripts

DNN_HLS: The DNN model implemented using Vivado High Level Synthesis (HLS), written in C++.

Host: Host code run on CPU for FPGA control

Overlay: The bitstream and tcl file for FPGA configuration

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Light-weighted neural network inference for object detection on small-scale FPGA board

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  • Jupyter Notebook 58.4%
  • C++ 20.1%
  • Tcl 11.4%
  • Python 10.1%