This template/tutorial records the necessary steps for developing a CUDA application, listed as follows.

1. Create a development container
2. Structure your source code
3. Setup CMake
4. Setup VS Code

If your project is developing on the eda38/eda39 server, skip the prerequisites.

Please install CUDA, CuDNN, Docker, and NVIDIA Container Toolkit on your machine.

1. Clone this repository.

git clone --recursive https://github.com/YanjenChen/CUDA-Programming-Template.git

2. Install the following VS Code extensions.

• Remote Development extension pack

3. Start VS Code, run the Dev Containers: Reopen in Container command from the Command Palette (F1) or quick actions Status bar item.
4. Build the example project

$ mkdir build && cd build
$ cmake ..
$ make -j8 && make install

5. Test the example project

$ python main.py

6. You are all set! Begin your development.

You can detail the usage of your application here.

You can detail the installation procedure of your application here.

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Yan-Jen Chen - [email protected]

• Developing inside a Container