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doc: simplify README structure and update content
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‎README.md

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@@ -18,18 +18,33 @@ AMD\* GPU, OpenPOWER\* Power ISA (PPC64), IBMz\* (s390x), and RISC-V.
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oneDNN is intended for deep learning applications and framework
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developers interested in improving application performance on CPUs and GPUs.
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Deep learning practitioners should use one of the
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[applications enabled with oneDNN](#applications-enabled-with-onednn).
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Deep learning practitioners should use one of the applications enabled with oneDNN:
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* [Apache SINGA](https://singa.apache.org)
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* [DeepLearning4J\*](https://deeplearning4j.konduit.ai)
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* [Flashlight\*](https://github.com/flashlight/flashlight)
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* [MATLAB\* Deep Learning Toolbox](https://www.mathworks.com/help/deeplearning)
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* [ONNX Runtime](https://onnxruntime.ai)
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* [OpenVINO(TM) toolkit](https://github.com/openvinotoolkit/openvino)
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* [PaddlePaddle\*](http://www.paddlepaddle.org)
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* [PyTorch\*](https://pytorch.org). Intel GPU support and additional
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optimizations are available with [Intel® Extension for PyTorch*].
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* [Tensorflow\*](https://www.tensorflow.org). Intel GPU support and additional
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optimizations are available with [Intel® Extension for TensorFlow*].
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[Intel® Extension for PyTorch*]: https://github.com/intel/intel-extension-for-pytorch
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[Intel® Extension for TensorFlow*]: https://github.com/intel/intel-extension-for-tensorflow
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[UXL Foundation]: http://www.uxlfoundation.org
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[oneAPI specification]: https://spec.oneapi.io
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[oneAPI specification]: https://oneapi-spec.uxlfoundation.org/specifications/oneapi/latest/elements/onednn/source/
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# Table of Contents
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- [Documentation](#documentation)
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- [Installation](#installation)
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- [System Requirements](#system-requirements)
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- [Applications Enabled with oneDNN](#applications-enabled-with-onednn)
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- [Installation](#installation)
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- [Validated Configurations](#validated-configurations)
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- [Governance](#governance)
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- [Support](#support)
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- [Contributing](#contributing)
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# Documentation
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* [Developer Guide] explains the programming model, supported functionality,
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and implementation details, and includes annotated examples.
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* [API Reference] provides a comprehensive reference of the library API.
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* [oneDNN Developer Guide and Reference] explains the programming
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model, supported functionality, implementation details, and includes
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annotated examples.
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* [API Reference] provides a comprehensive reference of the library
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API.
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* [Release Notes] explains the new features, performance
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optimizations, and improvements implemented in each version of
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oneDNN.
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[Developer Guide]: https://oneapi-src.github.io/oneDNN
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[oneDNN Developer Guide and Reference]: https://oneapi-src.github.io/oneDNN
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[API Reference]: https://oneapi-src.github.io/oneDNN/group_dnnl_api.html
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[Release Notes]: https://github.com/oneapi-src/oneDNN/releases
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# Installation
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Binary distribution of this software is available in:
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* [Anaconda]
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* [Intel oneAPI]
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The packages do not include library dependencies and these need to be resolved
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in the application at build time. See the [System Requirements] section below
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and the [Build Options] section in the [Developer Guide] for more details on
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CPU and GPU runtimes.
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If the configuration you need is not available, you can
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[build the library from source][Build from Source].
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[Anaconda]: https://anaconda.org/conda-forge/onednn
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[Intel oneAPI]: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onednn.html
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[System Requirements]: #system-requirements
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[Build Options]: https://oneapi-src.github.io/oneDNN/dev_guide_build_options.html
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[Build from Source]: https://oneapi-src.github.io/oneDNN/dev_guide_build.html
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# System Requirements
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[timeout detection and recovery]: https://learn.microsoft.com/en-us/windows-hardware/drivers/display/timeout-detection-and-recovery
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[TdrDelay]: https://learn.microsoft.com/en-us/windows-hardware/drivers/display/tdr-registry-keys#tdrdelay
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### Runtime Dependencies
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## Runtime Dependencies
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When oneDNN is built from source, the library runtime dependencies and specific
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versions are defined by the build environment.
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#### Linux
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### Linux
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Common dependencies:
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* GNU C Library (`libc.so`)
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| `DNNL_GPU_RUNTIME=OCL` | any | OpenCL loader (`libOpenCL.so`)
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| `DNNL_GPU_RUNTIME=SYCL` | Intel oneAPI DPC++ Compiler | Intel oneAPI DPC++ Compiler runtime (`libsycl.so`), OpenCL loader (`libOpenCL.so`), oneAPI Level Zero loader (`libze_loader.so`)
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#### Windows
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### Windows
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Common dependencies:
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* Microsoft Visual C++ Redistributable (`msvcrt.dll`)
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| `DNNL_GPU_RUNTIME=OCL` | any | OpenCL loader (`OpenCL.dll`)
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| `DNNL_GPU_RUNTIME=SYCL` | Intel oneAPI DPC++ Compiler | Intel oneAPI DPC++ Compiler runtime (`sycl.dll`), OpenCL loader (`OpenCL.dll`), oneAPI Level Zero loader (`ze_loader.dll`)
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#### macOS
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### macOS
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Common dependencies:
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* System C/C++ runtime (`libc++.dylib`, `libSystem.dylib`)
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| `DNNL_CPU_RUNTIME=OMP` | Intel C/C++ Compiler | Intel OpenMP runtime (`libiomp5.dylib`)
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| `DNNL_CPU_RUNTIME=TBB` | any | TBB (`libtbb.dylib`)
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### Validated Configurations
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# Installation
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You can download and install the oneDNN library using one of the following options:
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- Binary Distribution: You can download pre-built binary packages from
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the following sources:
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- [conda-forge]: If the configuration you need is not available on
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the conda-forge channel, you can build the library using the
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Source Distribution.
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- Intel oneAPI:
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- [Intel® oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.htm)
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- [Intel® oneDNN standalone package](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onednn-download.html)
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- Source Distribution: You can build the library from source by
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following the instructions on the [Build from Source] page.
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[conda-forge]: https://anaconda.org/conda-forge/onednn
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[System Requirements]: #system-requirements
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[Build Options]: https://oneapi-src.github.io/oneDNN/dev_guide_build_options.html
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[Build from Source]: https://oneapi-src.github.io/oneDNN/dev_guide_build.html
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# Validated Configurations
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x86-64 CPU engine was validated on RedHat\* Enterprise Linux 8 with
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* GNU Compiler Collection 8.5, 9.5, 11.1, 11.3
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[Intel Arc & Iris Xe Graphics Driver]: https://www.intel.com/content/www/us/en/download/785597/intel-arc-iris-xe-graphics-windows.html
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[Arm Compiler for Linux]: https://developer.arm.com/Tools%20and%20Software/Arm%20Compiler%20for%20Linux
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# Applications Enabled with oneDNN
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* [Apache\* MXNet](https://mxnet.apache.org)
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* [Apache SINGA](https://singa.apache.org)
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* [DeepLearning4J\*](https://deeplearning4j.konduit.ai)
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* [Flashlight\*](https://github.com/flashlight/flashlight)
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* [Korali](https://github.com/cselab/korali)
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* [MATLAB\* Deep Learning Toolbox](https://www.mathworks.com/help/deeplearning)
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* [ONNX Runtime](https://onnxruntime.ai)
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* [OpenVINO(TM) toolkit](https://github.com/openvinotoolkit/openvino)
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* [PaddlePaddle\*](http://www.paddlepaddle.org)
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* [PyTorch\*](https://pytorch.org). Intel GPU support and additional
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optimizations are available with [Intel Extension for PyTorch].
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* [Tensorflow\*](https://www.tensorflow.org). Intel GPU support and additional
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optimizations are available with [Intel Extension for Tensorflow].
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[Intel Extension for PyTorch]: https://github.com/intel/intel-extension-for-pytorch
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[Intel Extension for Tensorflow]: https://github.com/intel/intel-extension-for-tensorflow
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# Support
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[Milestones] section. If you are looking for a specific task to start,
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consider selecting from issues that are marked with the [help wanted] label.
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If you have an idea on how to improve the library:
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* For changes impacting the public API or library overall, such as adding new
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primitives or changes to the architecture, submit an [RFC pull request].
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* Ensure that the changes are consistent with the [code contribution guidelines]
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and [coding standards].
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* Ensure that you can build the product and run all the examples with your
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patch.
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* Submit a [pull request].
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For additional details, see [contribution guidelines](CONTRIBUTING.md). You can
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also contact oneDNN developers and maintainers via [UXL Foundation Slack] using
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[#onednn] channel.
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This project is intended to be a safe, welcoming space for collaboration, and
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contributors are expected to adhere to the
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See [contribution guidelines](CONTRIBUTING.md) to start contributing
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to oneDNN. You can also contact oneDNN developers and maintainers via
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[UXL Foundation Slack] using [#onednn] channel.
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This project is intended to be a safe, welcoming space for
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collaboration, and contributors are expected to adhere to the
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[Contributor Covenant](CODE_OF_CONDUCT.md) code of conduct.
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[RFC pull request]: https://github.com/oneapi-src/oneDNN/tree/rfcs
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[Milestones]: https://github.com/oneapi-src/oneDNN/milestones
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[help wanted]: https://github.com/oneapi-src/oneDNN/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22
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# License
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oneDNN is licensed under [Apache License Version 2.0](LICENSE). Refer to the
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"[LICENSE](LICENSE)" file for the full license text and copyright notice.
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oneDNN is licensed under [Apache License Version 2.0](LICENSE). Refer
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to the "[LICENSE](LICENSE)" file for the full license text and
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copyright notice.
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This distribution includes third party software governed by separate license
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terms.
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This distribution includes third party software governed by separate
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license terms.
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3-clause BSD license:
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* [Xbyak](https://github.com/herumi/xbyak)
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Interface](https://github.com/intel/metrics-discovery)
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* [spdlog](https://github.com/gabime/spdlog)
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This third party software, even if included with the distribution of
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the Intel software, may be governed by separate license terms, including
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without limitation, third party license terms, other Intel software license
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terms, and open source software license terms. These separate license terms
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govern your use of the third party programs as set forth in the
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"[THIRD-PARTY-PROGRAMS](THIRD-PARTY-PROGRAMS)" file.
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This third-party software, even if included with the distribution of
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the Intel software, may be governed by separate license terms,
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including without limitation,third party license terms, other Intel
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software license terms, and open source software license terms. These
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separate license terms govern your use of the third party programs as
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set forth in the "[THIRD-PARTY-PROGRAMS](THIRD-PARTY-PROGRAMS)" file.
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# Security
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[Security Policy](SECURITY.md) outlines our guidelines and procedures
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for ensuring the highest level of Security and trust for our users
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for ensuring the highest level of security and trust for our users
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who consume oneDNN.
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# Trademark Information

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