2de883c592
1. Update CK to its latest develop branch 2. `-mllvm -amdgpu-early-inline-all=true` is critical to CK's performance, ensure it is properly configured. - The flags are propagated from target `hip-lang::device`'s `INTERFACE_COMPILE_OPTIONS`, we must not manually add the flags. - Instead, we must ensure this target is properly configured by checking _CMAKE_HIP_DEVICE_RUNTIME_TARGET is set. TL,DR `hip-lang::device` sometime will be not be properly configured if our `CMAKE_PREFIX_PATH` is not configured carefully. In the CI docker, the configuration is in good state, but on dev machine it is not, which then silently result poor performance for kernels. We fixed it in this PR and add a guard to avoid unsuccessful future editing and to prevent convoluted debugging process. `_CMAKE_HIP_DEVICE_RUNTIME_TARGET ` is shared in `/opt/rocm/lib/cmake/hip-lang/hip-lang-config.cmake` and it is internal to [CMake](https://gitlab.kitware.com/cmake/cmake/-/merge_requests/6121/diffs), the variable name will not be changed in the foreseeable future. |
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ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started
General Information: onnxruntime.ai
Usage documention and tutorials: onnxruntime.ai/docs
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Build Pipeline Status
| System | CPU | GPU | EPs |
|---|---|---|---|
| Windows | |||
| Linux | |||
| Mac | |||
| Android | |||
| iOS | |||
| WebAssembly |
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.