https://github.com/jhurliman/jetson-crosscompile-template
A starting point for C++/CUDA cross-compilation and debugging for NVIDIA Jetson
https://github.com/jhurliman/jetson-crosscompile-template
Last synced: 2 months ago
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A starting point for C++/CUDA cross-compilation and debugging for NVIDIA Jetson
- Host: GitHub
- URL: https://github.com/jhurliman/jetson-crosscompile-template
- Owner: jhurliman
- License: mit
- Created: 2023-12-26T01:05:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-24T00:22:11.000Z (10 months ago)
- Last Synced: 2025-01-28T22:32:03.706Z (4 months ago)
- Language: C++
- Size: 136 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Remote C++ Development Template for NVIDIA Jetson - jetson-crosscompile-template
## Introduction
NVIDIA Jetson devices are great for edge computing, but the development experience of compiling and storing source code on device is not ideal. `jetson-crosscompile-template` simplifies the process of developing high-performance C++ applications for NVIDIA Jetson using clang and CMake in a Linux or WSL development environment with standardized tooling and workflows. A buffer abstraction API is provided that unifies various CUDA and NVMM memory models and provides Tegra, desktop CUDA, and CPU-only implementations to make your code write-once, run-anywhere. This template is designed to be a starting point for your next project, and includes the following features:
## Features
- **Cross-Compiling Support:** Don't waste time compiling on the Jetson. Build and deploy your application from your development machine.
- **Multiple Deployment Targets:** Easily switch between CPU, CUDA, and Tegra targets.
- **Remote Debugging:** Remote debugging with gdbserver and VSCode.
- **Hardware Buffer Abstractions:** RAII wrappers for CUDA and NVMM buffers with Tegra, CUDA desktop, and CPU-only implementations for on and off-device testing.
- **Modern C++ & CMake:** Utilizes recent standards in C++ and CMake for efficient development.
- **Dependency Management:** Easily add and manage dependencies with CPM. Provided scripts fetch the required NVIDIA packages for cross-compiling.
- **Testing:** Unit testing with Catch2 and CTest.
- **Linter Support:** Automatic linting with clang-format, cmake-format, and clang-tidy.
- **Static Analysis:** Static analysis with clang-tidy.
- **Code Coverage:** Code coverage with llvm-cov and gcovr.
- **Continuous Integration:** CI with GitHub Actions for automatic linting, building, testing, static analysis, and code coverage.
| | CPU | CUDA | NVMM |
| -------------- | :-: | :--: | :--: |
| GitHub Actions | ✅ | ❌ | ❌ |
| Linux/WSL | ✅ | ✅ | ❌ |
| Jetson | ✅ | ✅ | ✅ |
_Supported backends for different deployment targets. GitHub Actions can be extended to support CUDA and Tegra targets with [Custom Runners](https://docs.github.com/en/actions/hosting-your-own-runners/managing-self-hosted-runners/about-self-hosted-runners)._
## Getting Started
1. Clone This Template: Use [this template](https://github.com/jhurliman/jetson-crosscompile-template) to create a new repository, then git clone the new repository to your machine.
2. Set Up Your Environment: Follow the setup guide [here](docs/GettingStarted.md).
3. Build and Run: Use the [Makefile](Makefile) to build and run the project, or use the [VSCode Tasks](.vscode/tasks.json) to build, run, and debug.
## How to Contribute
Contributions of all kinds are welcome! Use GitHub issues and pull requests for bug reports, feature requests, and code contributions.
## License
This project is open source and available under the [MIT License](LICENSE). Developed by [John Hurliman](https://jhurliman.org/).
## TODO
- [x] ctest unit test
- [x] CPM dependency management
- [x] Add support for more Jetson devices
- [ ] fix <<<...>>> clang warning for CUDA kernel launch
- [ ] C++23