Orthognal Recurrent Neural Network on DE10-Nano.

This project is submitted to the Intel InnovateFPGA contest 2021-2022.

This model is trained on MNIST dataset i.e., given an image of a digit it predicts the number 0-9.

Similarly, in the audiomnist branch, the model is trained on audioMNIST dataset taken from here, it predicts the digit 0-9 given an audio file.

Install the FPGA-SoC-Linux by following the given instructions.

Make sure that the shared internet connection profile is setup from your host machine to the connected DE10-Nano. From you host machine run:

echo <your ip mask e.g 10.42.0. or 192.168.1.>{1..254} | xargs -P255 -n1 ping -s1 -c1 -W1 | grep ttl # To find the IP of the connected devices to the machine
ssh -L 9090:localhost:9090 fpga@<ip of the board> # you have to try all the listed IP to find the correct one :(
password is "fpga"

sudo apt update
sudo apt install -y rsync
sudo apt install libffi-dev
sudo apt-get install libjpeg-dev zlib1g-dev
pip3 install notebook pillow

Clone the project to the board directly using:

git clone https://github.com/ussamazahid96/ORNN-Nano.git

Or to copy the whole ORNN-Nano project to DE10 using rsync from your host machine run the follow from you host machine:

rsync -avP <Path to the ORNN-Nano folder>/ORNN-Nano fpga@<ip of the DE10>~/

Next upload the .rbf file and run the host.py to lauch the inference.

sudo -s
make install
python3 host.py
make uninstall # to unload the .rbf

Launch the notebook from the Host directory and open the given url in the browser of the host machine and run the ORNN-Demo.ipynb.

jupyter notebook --allow-root --no-browser --port=9090

Inspired from:

https://github.com/Xilinx/LSTM-PYNQ

https://github.com/Xilinx/finn-hlslib