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:
- The used approach to implement a Convolutional Neural Network (CNN)
- The elements that I took into account when choosing the neural network architecture
- 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!