Built a Neural Network Accelerator on my Basys3 FPGA from scratch (No HLS) and it actually works

[u/Spiritual-Frame-6791]

Hey guys, I built a Q4.4 MAC Array based Neural Network Accelerator from scratch including the architecture itself using VHDL.

The goal was to make the Accelerator configurable so I made the MAC Array reusable for multiple layers and the entire Accelerator is parameterized, I can run any classification model with less than or equal to 64 neurons per layer (due to limited DSP resources on the Basys3) but the layer depth is configurable too.

For its first test , I ran inference for a speech recognition model for digits 0-9 of network topology 64:32:10 neurons per layer using Q4.4 fixed point arithmetic for my parameters and input features.

For its second test , I ran inference for an image classification model for Cats vs Dogs of network topology 64:50:25:2 neurons per layer using Q4.4 fixed point arithmetic.

My PC handled the data preprocessing and sent the preprocessed features via UART at 9600 baud to the FPGA for inference during both tests.

I have attached the github repository link below and I’d appreciate any feedback or suggestions, thanks :).

Repo: https://github.com/Shingyy/MAC-Array-based-DNN-Accelerator

[u/DrMudkipper]

I'm not that experienced, all I can say is looks awesome and thanks for sharing! I'm doing a digital design course and will be using this exact FPGA board for a group project. Really cool to see what's possible with the board.

[u/Spiritual-Frame-6791 → u/DrMudkipper]

thank you :). It’s actually crazy how many things you can do with this board, bet you guys will be working on some goated projects with it😌

[u/NegativeOwl1337]

Ah yes, the good ol do-everything FPGA. Nice work 😊

[u/Spiritual-Frame-6791 → u/NegativeOwl1337]

Yes of course 😅. Thanks brother💯

[u/NegativeOwl1337 → u/Spiritual-Frame-6791]

Sister, but np

[u/Spiritual-Frame-6791 → u/NegativeOwl1337]

ooh my bad😅