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Update jetson docs (#23265)

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### Description
<!-- Describe your changes. -->
* Add more detail to instructions and build tips

Preview:
https://yf711.github.io/onnxruntime/docs/build/eps.html#nvidia-jetson-tx1tx2nanoxavierorin


### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Per https://github.com/microsoft/onnxruntime/issues/23113 to make docs
more accurate
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Yifan Li 2025-01-08 09:59:07 -08:00 committed by GitHub
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docs/build/eps.md vendored
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@ -153,7 +153,7 @@ Dockerfile instructions are available [here](https://github.com/microsoft/onnxru
### Build Instructions
{: .no_toc }
These instructions are for the latest [JetPack SDK 6](https://developer.nvidia.com/embedded/jetpack) for Jetson Orin.
These instructions are for the latest [JetPack SDK](https://developer.nvidia.com/embedded/jetpack).
1. Clone the ONNX Runtime repo on the Jetson host
@ -163,14 +163,15 @@ These instructions are for the latest [JetPack SDK 6](https://developer.nvidia.c
2. Specify the CUDA compiler, or add its location to the PATH.
1. Starting with **CUDA 11.8**, Jetson users on **JetPack 5.0+** can upgrade to the latest CUDA release without updating the JetPack version or Jetson Linux BSP (Board Support Package).
1. JetPack 5.x users can upgrade to the latest CUDA release without updating the JetPack version or Jetson Linux BSP (Board Support Package).
1. For JetPack 5.x users, CUDA 11.8 and GCC 11 are required to be updated, in order to build latest ONNX Runtime locally.
1. For JetPack 5.x users, CUDA>=11.8 and GCC>9.4 are required to be installed on and after ONNX Runtime 1.17.
2. Check [this official blog](https://developer.nvidia.com/blog/simplifying-cuda-upgrades-for-nvidia-jetson-users/) for CUDA upgrade instruction.
2. Check [this official blog](https://developer.nvidia.com/blog/simplifying-cuda-upgrades-for-nvidia-jetson-users/) for CUDA upgrade instruction (CUDA 12.2 has been verified on JetPack 5.1.2 on Jetson Xavier NX).
3. CUDA 12.x is only available to Jetson Orin and newer series (CUDA compute capability >= 8.7). Check [here](https://developer.nvidia.com/cuda-gpus#collapse5) for compute capability datasheet.
JetPack 6.0 comes preinstalled with CUDA 12.2
1. If there's no `libnvcudla.so` under `/usr/local/cuda-12.2/compat`: `sudo apt-get install -y cuda-compat-12-2` and add `export LD_LIBRARY_PATH="/usr/local/cuda-12.2/lib64:/usr/local/cuda-12.2/compat:$LD_LIBRARY_PATH"` to `~/.bashrc`.
3. Check [here](https://developer.nvidia.com/cuda-gpus#collapse5) for compute capability datasheet.
2. CMake can't automatically find the correct `nvcc` if it's not in the `PATH`. `nvcc` can be added to `PATH` via:
@ -186,9 +187,9 @@ These instructions are for the latest [JetPack SDK 6](https://developer.nvidia.c
3. Update TensorRT libraries
1. Jetpack 5.x supports up to TensorRT 8.5. Jetpack 6.0 is equipped with TensorRT 8.6 and can support TensorRT 10.
1. Jetpack 5.x supports up to TensorRT 8.5. Jetpack 6.x are equipped with TensorRT 8.6-10.3.
2. Jetpack 6.0 users can download latest TensorRT 10 TAR package for jetpack on [TensorRT SDK website](https://developer.nvidia.com/tensorrt/download/10x).
2. Jetpack 6.x users can download latest TensorRT 10 TAR package for **jetpack** on [TensorRT SDK website](https://developer.nvidia.com/tensorrt/download/10x).
3. Check [here](../execution-providers/TensorRT-ExecutionProvider.md#requirements) for TensorRT/CUDA support matrix among all ONNX Runtime versions.
@ -200,7 +201,7 @@ These instructions are for the latest [JetPack SDK 6](https://developer.nvidia.c
libpython3.8-dev python3-pip python3-dev python3-setuptools python3-wheel
```
4. Cmake is needed to build ONNX Runtime. The minimum required CMake version is 3.26 (version 3.27.4 has been tested). This can be either installed by:
4. Cmake is needed to build ONNX Runtime. The minimum required CMake version is 3.26. This can be either installed by:
1. (Unix/Linux) Build from source. Download sources from [https://cmake.org/download/](https://cmake.org/download/)
and follow [https://cmake.org/install/](https://cmake.org/install/) to build from source.
@ -220,7 +221,11 @@ These instructions are for the latest [JetPack SDK 6](https://developer.nvidia.c
* By default, `onnxruntime-gpu` wheel file will be captured under `path_to/onnxruntime/build/Linux/Release/dist/` (build path can be customized by adding `--build_dir` followed by a customized path to the build command above).
* For a portion of Jetson devices like the Xavier series, higher power mode involves more cores (up to 6) to compute but it consumes more resource when building ONNX Runtime. Set `--parallel 2` or smaller in the build command if system is hanging and OOM happens.
* Append `--skip_tests --cmake_extra_defines 'CMAKE_CUDA_ARCHITECTURES=72;87' 'onnxruntime_BUILD_UNIT_TESTS=OFF' 'onnxruntime_USE_FLASH_ATTENTION=OFF'
'onnxruntime_USE_MEMORY_EFFICIENT_ATTENTION=OFF'` to the build command to opt out optional features and reduce build time.
* For a portion of Jetson devices like the Xavier series, higher power mode involves more cores (up to 6) to compute but it consumes more resource when building ONNX Runtime. Set `--parallel 1` in the build command if OOM happens and system is hanging.
## oneDNN
See more information on oneDNN (formerly DNNL) [here](../execution-providers/oneDNN-ExecutionProvider.md).