For full contest details, please see the 2022 DAC System Design Contest page.

For general questions regarding this contest, please use the Piazza page: piazza.com/dac_2018/winterterm12021/dacsdc2021

• Download the PYNQ 2.7 Ultra96v2 board image from http://www.pynq.io/board.html
• Follow the instructions to image the SD card at https://pynq.readthedocs.io/en/latest/getting_started/pynq_image.html.
• Follow the instructions to setup and connect to the board at https://ultra96-pynq.readthedocs.io/en/latest/getting_started.html.

The get started, users have to run the following command on the Ultra96 board:

cd /home/xilinx/jupyter_notebooks
git clone https://github.com/jgoeders/dac_sdc_2022.git

Remember the user name and password are both xilinx for super user.

After the above step is completed successfully, you will see a folder dac_sdc_2022 under your jupyter notebook dashboard. Open the sample_team/dac_sdc.ipynb notebook for directions on where to begin.

1. sample_team: This folder contains files for a sample team. This includes a .bit and .tcl file that defines the hardware, and a .ipynb jupyter notebook, and a hw folder that is used to create a Vivado project. You should create a new folder for your team, where you will keep all of your files.

2. images: All the test images are stored in this folder. Replace the example images in this directory with the full training set.

3. result: The results contain the output xml produced when execution is complete, and contains the runtime, energy usage, and predicted location of each object in each image.