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18620931a8
and create a README.md symlink for better formatting when viewing on Github. Signed-off-by: Matt Madison <matt@madison.systems>
84 lines
3.2 KiB
Plaintext
84 lines
3.2 KiB
Plaintext
OpenEmbedded/Yocto BSP layer for NVIDIA Jetson TX1/TX2/AGX Xavier/Nano
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======================================================================
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Boards supported:
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* Jetson-TX1 development kit (Linux4Tegra R32.3.1, JetPack 4.3)
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* Jetson-TX2 development kit (Linux4Tegra R32.3.1, JetPack 4.3)
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* Jetson AGX Xavier development kit (Linux4Tegra R32.3.1, JetPack 4.3)
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* Jetson Nano development kit (Linux4Tegra R32.3.1, JetPack 4.3)
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Also supported thanks to community support:
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* Jetson-TX2i module (Linux4Tegra R32.3.1, JetPack 4.3)
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* Jetson-TX2 4GB module (Linux4Tegra R32.3.1, JetPack 4.3)
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* Jetson AGX Xavier 8GB module (Linux4Tegra R32.3.1, JetPack 4.3)
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This layer depends on:
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URI: git://git.openembedded.org/openembedded-core
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branch: master
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LAYERSERIES_COMPAT: zeus
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PLEASE NOTE
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-----------
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* Starting with JetPack 4.2, packages outside the L4T BSP can
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only be downloaded with an NVIDIA Developer Network login.
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So to use CUDA 10, cuDNN, and any other packages that require
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a Devnet login, you **must** create a Devnet account and
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download the JetPack packages you need for your builds using
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NVIDIA SDK Manager.
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You must then set the variable NVIDIA_DEVNET_MIRROR to
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"file://path/to/the/downloads" in your build configuration
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(e.g., local.conf) to make them available to your bitbake
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builds. This can be the NVIDIA SDK Manager downloads
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directory, `/home/$USER/Downloads/nvidia/sdkm_downloads`
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**Note** Starting with L4T R32.3 and JetPack 4.3, The Tegra
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Multimedia API kit has moved to JetPack, so **all builds**
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now require you to set up an SDK Manager downloads area.
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* The SDK Manager downloads a different package of CUDA host-side
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tools depending on whether you are running Ubuntu 16.04
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or 18.04. If you downloaded the Ubuntu 16.04 package, you
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should add
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CUDA_BINARIES_NATIVE = "cuda-binaries-ubuntu1604-native"
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to your build configuration so the CUDA recipes can find
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them. Otherwise, the recipes will default to looking for
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the Ubuntu 18.04 package.
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* The TensorRT 6.0.1 packages for Xavier are different from
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those for TX1/TX2, even though the deb files have the same
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name. To prevent mixups during the build, the recipe here
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expects to find the Xavier packages in a `DLA` subdirectory
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under `${NVIDIA_DEVNET_MIRROR}`, and non-Xavier packages
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in a `NoDLA` subdirectory.
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If you need to include TensorRT in your builds, you **must**
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create the subdirectory and move all of the TensorRT packages
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downloaded by the SDK Manager there. Xavier example:
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$ cd ~/Downloads/nvidia/sdkm_downloads
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$ mkdir DLA
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$ mv tensorrt*.deb libnvinfer*.deb DLA/
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* CUDA 10 supports up through gcc 7 only, and some NVIDIA-provided
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binary libraries appear to be compiled with g++ 7 and cause linker
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failures when building applications with g++ 6, so **only** gcc 7
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should be used if you intend to use CUDA. See the following wiki
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pages for instructions on including gcc 7 in your builds:
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(https://github.com/madisongh/meta-tegra/wiki/Using-gcc7-from-the-contrib-layer)
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(https://github.com/madisongh/meta-tegra/wiki/Using-linaro-gcc7-for-CUDA-support)
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Contributing
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------------
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Please use GitHub (https://github.com/madisongh/meta-tegra) to submit
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issues or pull requests, or add to the documentation on the wiki.
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Contributions are welcome!
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