CNN using HLS

I am pleased to announce the release of the code for the article “How to Implement a Convolutional Neural Network Using High-Level Synthesis”.


The previous article discussed three main aspects:

  1. The used approach to implement a Convolutional Neural Network (CNN)
  2. The elements that I took into account when choosing the neural network architecture
  3. The specific High-Level Synthesis constructs that helped to achieve the targeted performance.


Now you can download the code from GitHub.
The GIT repository contains:

  • The CNN implementation
  • The python codes used for training
  • Modules for each type of layer (convolutional, pooling and fully connected) used for development and testing
  • Short guide on how to set up and run the code

The CNN code is provided as an OpenSource implementation under Apache License 2.0.
I welcome your feedback!


SP March 10th, 2020 21:14:39

Sorry, but I do not see the python codes used for training.

Pedro April 17th, 2020 14:31:36

Hello Sergiu Duda,

Please tell me if you can post the full version of your diploma thesis for review on github, or is it forbidden?

Thank you in advance.

Leave a Comment:

Your comment will be visible after approval.

(will not be published)

This site uses Akismet to reduce spam. Learn how your comment data is processed.