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Version 1.14 docs sweep (#14789)

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21
docs/build/eps.md vendored
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@ -45,7 +45,7 @@ The onnxruntime code will look for the provider shared libraries in the same loc
### Prerequisites
{: .no_toc }
* Install [CUDA](https://developer.nvidia.com/cuda-toolkit) and [cuDNN](https://developer.nvidia.com/cudnn).
* Install [CUDA](https://developer.nvidia.com/cuda-toolkit) and [cuDNN](https://developer.nvidia.com/cudnn) according to the [version compatibility matrix](../execution-providers/CUDA-ExecutionProvider.md#requirements).
* The path to the CUDA installation must be provided via the CUDA_PATH environment variable, or the `--cuda_home` parameter.
* The path to the cuDNN installation (include the `cuda` folder in the path) must be provided via the cuDNN_PATH environment variable, or `--cudnn_home` parameter. The cuDNN path should contain `bin`, `include` and `lib` directories.
* The path to the cuDNN bin directory must be added to the PATH environment variable so that cudnn64_8.dll is found.
@ -68,17 +68,18 @@ The onnxruntime code will look for the provider shared libraries in the same loc
A Dockerfile is available [here](https://github.com/microsoft/onnxruntime/blob/main/dockerfiles#cuda).
### Notes
### Notes on older versions of ONNX Runtime, CUDA and Visual Studio
{: .no_toc }
* Depending on compatibility between the CUDA, cuDNN, and Visual Studio 2017 versions you are using, you may need to explicitly install an earlier version of the MSVC toolset.
* CUDA 10.0 is [known to work](https://devblogs.microsoft.com/cppblog/cuda-10-is-now-available-with-support-for-the-latest-visual-studio-2017-versions/) with toolsets from 14.11 up to 14.16 (Visual Studio 2017 15.9), and should continue to work with future Visual Studio versions
* CUDA 9.2 is known to work with the 14.11 MSVC toolset (Visual Studio 15.3 and 15.4)
* To install the 14.11 MSVC toolset, see [this page](https://blogs.msdn.microsoft.com/vcblog/2017/11/15/side-by-side-minor-version-msvc-toolsets-in-visual-studio-2017).
* To use the 14.11 toolset with a later version of Visual Studio 2017 you have two options:
1. Setup the Visual Studio environment variables to point to the 14.11 toolset by running vcvarsall.bat, prior to running the build script. e.g. if you have VS2017 Enterprise, an x64 build would use the following command `"C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" amd64 -vcvars_ver=14.11` For convenience, .\build.amd64.1411.bat will do this and can be used in the same way as .\build.bat. e.g. ` .\build.amd64.1411.bat --use_cuda`
* Depending on compatibility between the CUDA, cuDNN, and Visual Studio versions you are using, you may need to explicitly install an earlier version of the MSVC toolset.
* For older version of ONNX Runtime and CUDA, and Visual Studio:
* CUDA 10.0 is [known to work](https://devblogs.microsoft.com/cppblog/cuda-10-is-now-available-with-support-for-the-latest-visual-studio-2017-versions/) with toolsets from 14.11 up to 14.16 (Visual Studio 2017 15.9), and should continue to work with future Visual Studio versions
* CUDA 9.2 is known to work with the 14.11 MSVC toolset (Visual Studio 15.3 and 15.4)
* To install the 14.11 MSVC toolset, see [this page](https://blogs.msdn.microsoft.com/vcblog/2017/11/15/side-by-side-minor-version-msvc-toolsets-in-visual-studio-2017).
* To use the 14.11 toolset with a later version of Visual Studio 2017 you have two options:
1. Setup the Visual Studio environment variables to point to the 14.11 toolset by running vcvarsall.bat, prior to running the build script. e.g. if you have VS2017 Enterprise, an x64 build would use the following command `"C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" amd64 -vcvars_ver=14.11` For convenience, .\build.amd64.1411.bat will do this and can be used in the same way as .\build.bat. e.g. ` .\build.amd64.1411.bat --use_cuda`
2. Alternatively, if you have CMake 3.13 or later you can specify the toolset version via the `--msvc_toolset` build script parameter. e.g. `.\build.bat --msvc_toolset 14.11`
2. Alternatively, if you have CMake 3.13 or later you can specify the toolset version via the `--msvc_toolset` build script parameter. e.g. `.\build.bat --msvc_toolset 14.11`
* If you have multiple versions of CUDA installed on a Windows machine and are building with Visual Studio, CMake will use the build files for the highest version of CUDA it finds in the BuildCustomization folder.
e.g. C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\Common7\IDE\VC\VCTargets\BuildCustomizations\.
@ -94,7 +95,7 @@ See more information on the TensorRT Execution Provider [here](../execution-prov
{: .no_toc }
* Install [CUDA](https://developer.nvidia.com/cuda-toolkit) and [cuDNN](https://developer.nvidia.com/cudnn)
* The TensorRT execution provider for ONNX Runtime is built and tested with CUDA 10.2/11.0/11.1/11.4/11.6 and cuDNN 8.0/cuDNN 8.2/cuDNN 8.4.
* The TensorRT execution provider for ONNX Runtime is built and tested with CUDA 11.0/11.1/11.4/11.6 and cuDNN 8.0/cuDNN 8.2/cuDNN 8.4.
* The path to the CUDA installation must be provided via the CUDA_PATH environment variable, or the `--cuda_home` parameter. The CUDA path should contain `bin`, `include` and `lib` directories.
* The path to the CUDA `bin` directory must be added to the PATH environment variable so that `nvcc` is found.
* The path to the cuDNN installation (path to folder that contains libcudnn.so) must be provided via the cuDNN_PATH environment variable, or `--cudnn_home` parameter.

5
docs/execution-providers/CUDA-ExecutionProvider.md
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@ -31,7 +31,7 @@ Please reference [Nvidia CUDA Minor Version Compatibility](https://docs.nvidia.c
|ONNX Runtime|CUDA|cuDNN|Notes|
|---|---|---|---|
|1.13|11.6|8.2.4 (Linux)<br/>8.5.0.96 (Windows)|libcudart 11.4.43<br/>libcufft 10.5.2.100<br/>libcurand 10.2.5.120<br/>libcublasLt 11.6.5.2<br/>libcublas 11.6.5.2<br/>libcudnn 8.2.4|
|1.14<br/>1.13.1<br/>1.13|11.6|8.2.4 (Linux)<br/>8.5.0.96 (Windows)|libcudart 11.4.43<br/>libcufft 10.5.2.100<br/>libcurand 10.2.5.120<br/>libcublasLt 11.6.5.2<br/>libcublas 11.6.5.2<br/>libcudnn 8.2.4|
|1.12<br/>1.11|11.4|8.2.4 (Linux)<br/>8.2.2.26 (Windows)|libcudart 11.4.43<br/>libcufft 10.5.2.100<br/>libcurand 10.2.5.120<br/>libcublasLt 11.6.5.2<br/>libcublas 11.6.5.2<br/>libcudnn 8.2.4|
|1.10|11.4|8.2.4 (Linux)<br/>8.2.2.26 (Windows)|libcudart 11.4.43<br/>libcufft 10.5.2.100<br/>libcurand 10.2.5.120<br/>libcublasLt 11.6.1.51<br/>libcublas 11.6.1.51<br/>libcudnn 8.2.4|
|1.9|11.4|8.2.4 (Linux)<br/>8.2.2.26 (Windows)|libcudart 11.4.43<br/>libcufft 10.5.2.100<br/>libcurand 10.2.5.120<br/>libcublasLt 11.6.1.51<br/>libcublas 11.6.1.51<br/>libcudnn 8.2.4|
@ -88,7 +88,8 @@ Default value: true
Check [tuning performance for convolution heavy models](../performance/tune-performance.md#convolution-heavy-models-and-the-cuda-ep) for details on what this flag does.
This flag is only supported from the V2 version of the provider options struct when used using the C API. The V2 provider options struct can be created using [this](https://onnxruntime.ai/docs/api/c/struct_ort_api.html#a0d29cbf555aa806c050748cf8d2dc172) and updated using [this](https://onnxruntime.ai/docs/api/c/struct_ort_api.html#a4710fc51f75a4b9a75bde20acbfa0783). Please take a look at the sample below for an example.
Default value: 0
Default value: 1, for versions 1.14 and later
0, for previous versions
### cudnn_conv1d_pad_to_nc1d
Check [convolution input padding in the CUDA EP](../performance/tune-performance.md#convolution-input-padding-in-the-cuda-ep) for details on what this flag does.

1
docs/execution-providers/MIGraphX-ExecutionProvider.md
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@ -30,6 +30,7 @@ Pre-built binaries of ONNX Runtime with MIGraphX EP are published for most langu
|ONNX Runtime|MIGraphX|
|---|---|
|main|5.4|
|1.14|5.4|
|1.13|5.4|
|1.13|5.3.2|
|1.12|5.2.3|

2
docs/reference/releases-servicing.md
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@ -7,7 +7,7 @@ nav_order: 1
# ONNX Runtime releases
The current ONNX Runtime release is [1.14](https://github.com/microsoft/onnxruntime/releases/tag/v1.14.0).
The current ONNX Runtime release is [1.14.0](https://github.com/microsoft/onnxruntime/releases/tag/v1.14.0).
The next release is ONNX Runtime release 1.15.

2
docs/tutorials/csharp/csharp-gpu.md
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@ -25,7 +25,7 @@ See this table for supported versions:
| ONNX Runtime Version | CUDA Toolkit Version | cuDNN Version|
|----------------------|----------------------|--------------|
| 1.13 | 11.6 | 8.5.0.96 |
| 1.13 - 1.14 | 11.6 | 8.5.0.96 |
| 1.9 - 1.12 | 11.4 | 8.2.2.26 |
NOTE: Full table can be found [here](https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements)