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Update build.md with recent changes (#6708)
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Nat Kershaw (MSFT)
GitHub
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1 changed files with 66 additions and 21 deletions
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@ -108,6 +108,7 @@ GCC 4.x and below are not supported.
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|**Use OpenMP**|--use_openmp|OpenMP will parallelize some of the code for potential performance improvements. This is not recommended for running on single threads.|
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|**Build using parallel processing**|--parallel|This is strongly recommended to speed up the build.|
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|**Build Shared Library**|--build_shared_lib||
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|**Enable Training support**|--enable_training||
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#### APIs and Language Bindings
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@ -341,21 +342,21 @@ See more information on the OpenVINO Execution Provider [here](../reference/exec
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##### Prerequisites
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1. Install the Intel<sup>®</sup> Distribution of OpenVINO<sup>TM</sup> Toolkit **Release 2021.1** for the appropriate OS and target hardware :
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1. Install the Intel<sup>®</sup> Distribution of OpenVINO<sup>TM</sup> Toolkit **Release 2021.2** for the appropriate OS and target hardware:
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* [Linux - CPU, GPU, VPU, VAD-M](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-linux)
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* [Linux - FPGA](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-linux-fpga)
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* [Windows - CPU, GPU, VPU, VAD-M](https://software.intel.com/en-us/openvino-toolkit/choose-download/free-download-windows).
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Follow [documentation](https://docs.openvinotoolkit.org/2021.1/index.html) for detailed instructions.
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Follow [documentation](https://docs.openvinotoolkit.org/2021.2/index.html) for detailed instructions.
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*2021.1 is the recommended OpenVINO version. [OpenVINO 2020.2](https://docs.openvinotoolkit.org/2020.2/index.html) is minimal OpenVINO version requirement.*
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*The minimum ubuntu version to support 2021.1 is 18.04.*
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*2021.2 is the recommended OpenVINO version. [OpenVINO 2020.3](https://docs.openvinotoolkit.org/2020.2/index.html) is minimal OpenVINO version requirement.*
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*The minimum ubuntu version to support 2021.2 is 18.04.*
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2. Configure the target hardware with specific follow on instructions:
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* To configure Intel<sup>®</sup> Processor Graphics(GPU) please follow these instructions: [Windows](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_windows.html#Install-GPU), [Linux](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_linux.html#additional-GPU-steps)
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* To configure Intel<sup>®</sup> Movidius<sup>TM</sup> USB, please follow this getting started guide: [Linux](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_linux.html#additional-NCS-steps)
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* To configure Intel<sup>®</sup> Vision Accelerator Design based on 8 Movidius<sup>TM</sup> MyriadX VPUs, please follow this configuration guide: [Windows](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_windows.html#hddl-myriad), [Linux](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_linux.html#install-VPU). Follow steps 3 and 4 to complete the configuration.
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* To configure Intel<sup>®</sup> Vision Accelerator Design with an Intel<sup>®</sup> Arria<sup>®</sup> 10 FPGA, please follow this configuration guide: [Linux](https://docs.openvinotoolkit.org/2021.1/openvino_docs_install_guides_installing_openvino_linux_fpga.html)
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* To configure Intel<sup>®</sup> Processor Graphics(GPU) please follow these instructions: [Windows](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_windows.html#Install-GPU), [Linux](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_linux.html#additional-GPU-steps)
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* To configure Intel<sup>®</sup> Movidius<sup>TM</sup> USB, please follow this getting started guide: [Linux](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_linux.html#additional-NCS-steps)
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* To configure Intel<sup>®</sup> Vision Accelerator Design based on 8 Movidius<sup>TM</sup> MyriadX VPUs, please follow this configuration guide: [Windows](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_windows.html#hddl-myriad), [Linux](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_linux.html#install-VPU). Follow steps 3 and 4 to complete the configuration.
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* To configure Intel<sup>®</sup> Vision Accelerator Design with an Intel<sup>®</sup> Arria<sup>®</sup> 10 FPGA, please follow this configuration guide: [Linux](https://docs.openvinotoolkit.org/2021.2/openvino_docs_install_guides_installing_openvino_linux_fpga.html)
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3. Initialize the OpenVINO environment by running the setupvars script as shown below:
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* For Linux run:
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@ -376,18 +377,20 @@ See more information on the OpenVINO Execution Provider [here](../reference/exec
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##### Build Instructions
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###### Windows
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```
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.\build.bat --config RelWithDebInfo --use_openvino <hardware_option>
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.\build.bat --config RelWithDebInfo --use_openvino <hardware_option> --build_shared_lib
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```
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*Note: The default Windows CMake Generator is Visual Studio 2017, but you can also use the newer Visual Studio 2019 by passing `--cmake_generator "Visual Studio 16 2019"` to `.\build.bat`*
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###### Linux
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```
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./build.sh --config RelWithDebInfo --use_openvino <hardware_option>
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```bash
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./build.sh --config RelWithDebInfo --use_openvino <hardware_option> --build_shared_lib
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```
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<code>--use_openvino</code>: Builds the OpenVINO Execution Provider in ONNX Runtime.
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* `--use_openvino` builds the OpenVINO Execution Provider in ONNX Runtime.
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* `<hardware_option>`: Specifies the default hardware target for building OpenVINO Execution Provider. This can be overriden dynamically at runtime with another option (refer to [OpenVINO-ExecutionProvider.md](../reference/execution-providers/OpenVINO-ExecutionProvider.md) for more details on dynamic device selection). Below are the options for different Intel target devices.
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| Hardware Option | Target Device |
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@ -598,10 +601,11 @@ The Batch Normalization operator is set by default to use the CPU execution prov
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./build.sh --use_armnn --armnn_bn
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```
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To use a library outside the normal environment you can set a custom path by using --armnn_home and --armnn_libs tags that defines the path to the ArmNN home directory and the build directory respectively.
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To use a library outside the normal environment you can set a custom path by providing the --armnn_home and --armnn_libs parameters to define the path to the ArmNN home directory and build directory respectively.
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The ARM Compute Library home directory and build directory must also be available, and can be specified if needed using --acl_home and --acl_libs respectively.
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```bash
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./build.sh --use_armnn --armnn_home /path/to/ComputeLibrary --armnn_libs /path/to/build
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./build.sh --use_armnn --armnn_home /path/to/armnn --armnn_libs /path/to/armnn/build --acl_home /path/to/ComputeLibrary --acl_libs /path/to/acl/build
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```
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---
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@ -736,14 +740,17 @@ ORT_DEBUG_NODE_IO_DUMP_DATA_TO_FILES=1
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---
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### Architectures
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#### x86
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#### 64-bit x86
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Also known as [x86_64](https://en.wikipedia.org/wiki/X86-64) or AMD64. This is the default.
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#### 32-bit x86
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##### Build Instructions
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###### Windows
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* add `--x86` argument when launching `.\build.bat`
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###### Linux
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* Must be built on a x86 OS
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* add --x86 argument to build.sh
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(Not officially supported)
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---
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@ -1231,8 +1238,31 @@ Dockerfile instructions are available [here](https://github.com/microsoft/onnxru
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---
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## Training
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### CPU
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### CUDA
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#### Build Instructions
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To build ORT with training support add `--enable_training` build instruction.
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All other build options are the same for inferencing as they are for training.
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##### Windows
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```
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.\build.bat --config RelWithDebInfo --build_shared_lib --parallel --enable_training
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```
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The default Windows CMake Generator is Visual Studio 2017, but you can also use the newer Visual Studio 2019 by passing
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`--cmake_generator "Visual Studio 16 2019"` to `.\build.bat`
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##### Linux/macOS
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```
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./build.sh --config RelWithDebInfo --build_shared_lib --parallel --enable_training
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```
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### GPU / CUDA
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#### Prerequisites
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The default NVIDIA GPU build requires CUDA runtime libraries installed on the system:
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@ -1267,7 +1297,7 @@ These dependency versions should reflect what is in [Dockerfile.training](https:
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This produces the .whl file in `./build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training.
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### ROCM
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### GPU / ROCM
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#### Prerequisites
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The default AMD GPU build requires ROCM software toolkit installed on the system:
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@ -1287,4 +1317,19 @@ These dependency versions should reflect what is in [Dockerfile.training](./dock
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* Change to the ONNX Runtime repo base folder: `cd onnxruntime`
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* Run `./build.sh --config RelWithDebInfo --enable_training --build_wheel --use_rocm --rocm_home /opt/rocm --nccl_home /opt/rocm --mpi_home <location for openmpi>`
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This produces the .whl file in `./build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training.
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This produces the .whl file in `./build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training.
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### DNNL and MKLML
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#### Build Instructions
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##### Linux
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`./build.sh --enable_training --use_dnnl`
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##### Windows
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`.\build.bat --enable_training --use_dnnl`
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Add `--build_wheel` to build the ONNX Runtime wheel
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This will produce a .whl file in `build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training
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