Project Title
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Prerequisites
Install Docker for your platform
- Windows - https://docs.docker.com/toolbox/toolbox_install_windows/
- Mac - https://docs.docker.com/docker-for-mac/install/
- Linux - Please consult your distro
Installing
Ensure the Docker service is running and execute the following
chmod +x start.sh ./start.sh
## Deployment
TODO - Add additional notes about how to deploy this on a live system and manage it (docker-compose up etc)
## Contributing
TODO - Add a CONTRIBUTING.md file and link here
## Authors
* **Brad McCormack** - *Initial work* - [PurpleBooth](https://github.com/PurpleBooth)
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
## Acknowledgments
Thanks to Nvidia for their Docker base images
* https://hub.docker.com/r/nvidia/cuda/
* https://github.com/NVIDIA/nvidia-docker/wiki/Image-inspection#nvidia-docker
* https://github.com/eywalker/nvidia-docker-compose
## TODO
* Use Alpine as the base Docker image and port Nvidia build instructions over to reduce the image size
* Roll my own cpu image and don't rely on servethehome/monero_dwarfpool:zen as it's not obvious how that image was constructed (I couldn't find the Dockerfile)
* AMD GPU support
* Customize the mining pool via environment variables or Docker tags
* Consider creating a very simple web service in Go with a web view to control the containers and observe progress (Without using Docker attach etc)
* See if there are faster GPU mining programs and swap out ccminer (xmrminer ??)
* Consider CUDA_CACHE_PATH