[![Ubuntu 22.04](https://github.com/ROCm/rocprofiler-compute/actions/workflows/ubuntu-jammy.yml/badge.svg)](https://github.com/ROCm/rocprofiler-compute/actions/workflows/ubuntu-jammy.yml) [![RHEL 8](https://github.com/ROCm/rocprofiler-compute/actions/workflows/rhel-8.yml/badge.svg)](https://github.com/ROCm/rocprofiler-compute/actions/workflows/rhel-8.yml) [![Instinct](https://github.com/ROCm/rocprofiler-compute/actions/workflows/mi-rhel9.yml/badge.svg)](https://github.com/ROCm/rocprofiler-compute/actions/workflows/mi-rhel9.yml) [![Docs](https://github.com/ROCm/rocprofiler-compute/actions/workflows/docs.yml/badge.svg)](https://rocm.github.io/rocprofiler-compute/) [![DOI](https://zenodo.org/badge/561919887.svg)](https://zenodo.org/badge/latestdoi/561919887) # ROCm Compute Profiler ## General ROCm Compute Profiler is a system performance profiling tool for machine learning/HPC workloads running on AMD MI GPUs. The tool presently targets usage on MI100, MI200, and MI300 accelerators. * For more information on available features, installation steps, and workload profiling and analysis, please refer to the online [documentation](https://rocm.docs.amd.com/projects/rocprofiler-compute/en/latest/). * ROCm Compute Profiler is an AMD open source research project and is not supported as part of the ROCm software stack. We welcome contributions and feedback from the community. Please see the [CONTRIBUTING.md](CONTRIBUTING.md) file for additional details on our contribution process. * Licensing information can be found in the [LICENSE](LICENSE) file. ## Development ROCm Compute Profiler follows a [main-dev](https://nvie.com/posts/a-successful-git-branching-model/) branching model. As a result, our latest stable release is shipped from the `amd-mainline` branch, while new features are developed in our `develop` branch. Users may checkout `amd-staging` to preview upcoming features. ## Testing To quickly get the environment (bash shell) for building and testing, run the following commands: * `cd utils/docker_env` * `docker compose run app` Inside the docker container, clean, build and install the project with tests enabled: ``` rm -rf build install && cmake -B build -D CMAKE_INSTALL_PREFIX=install -D ENABLE_TESTS=ON -D INSTALL_TESTS=ON -DENABLE_COVERAGE=ON -S . && cmake --build build --target install --parallel 8 ``` Note that per the above command, build assets will be stored under `build` directory and installed assets will be stored under `install` directory. Then, to run the automated test suite, run the following command: ``` ctest ``` For manual testing, you can find the executable at `install/bin/rocprof-compute` NOTE: This Dockerfile uses `rocm/dev-ubuntu-22.04` as the base image ## How to Cite This software can be cited using a Zenodo [DOI](https://doi.org/10.5281/zenodo.7314631) reference. A BibTex style reference is provided below for convenience: ``` @software{xiaomin_lu_2022_7314631 author = {Xiaomin Lu and Cole Ramos and Fei Zheng and Karl W. Schulz and Jose Santos and Keith Lowery and Nicholas Curtis and Cristian Di Pietrantonio}, title = {ROCm/rocprofiler-compute: v3.0.0 (01 November 2024)}, month = November, year = 2024, publisher = {Zenodo}, version = {v3.0.0}, doi = {10.5281/zenodo.7314631}, url = {https://doi.org/10.5281/zenodo.7314631} } ```