Original project here

• ultranet.cpp/ultranet

• Period: 8
• Uncertainty: defult

To do high-level synthesis on the accelerator and export it as a Vivado IP, simply use make build.

You can use c simulation to compare the results from the C model with the PyTorch one, using make csim. The results from each layer and the diff results will be dumped to ultranet_csim directory. The command-line output would show the Sum of Squared Error (SSE) and Mean of Squared Error (MSE) of each layer. The path to the model's state dict is hard-coded at:

csim.py, line26: state_dict = torch.load('../../export/4bitfs.pt', map_location = torch.device('cpu'))['model']

Modify it if necessary.

Before running using your account on our server, be sure to modify the PROJ_ROOT in the makefile:

Makefile line21: PROJ_ROOT = /home/yd383/dac-sdc

change this to point to the root of the git repo.

The generated RTL can be verified with a custom cosim flow: make cosim. It compares the RTL model with the C++ code to make sure they are equivalent. NOTE: it does not compare the RTL model with the PyTorch model.

• https://github.com/fpgasystems/spooNN.git
• https://github.com/Xilinx/BNN-PYNQ.git