From ea05215513a3ddd7bb6ef6667bc09a233c9cd456 Mon Sep 17 00:00:00 2001 From: Matt Madison Date: Wed, 8 Jan 2020 16:10:52 -0800 Subject: [PATCH] README, README.md: swap content and symlink Signed-off-by: Matt Madison --- README | 84 +------------------------------------------------------ README.md | 84 ++++++++++++++++++++++++++++++++++++++++++++++++++++++- 2 files changed, 84 insertions(+), 84 deletions(-) mode change 100644 => 120000 README mode change 120000 => 100644 README.md diff --git a/README b/README deleted file mode 100644 index 28347e63..00000000 --- a/README +++ /dev/null @@ -1,83 +0,0 @@ -OpenEmbedded/Yocto BSP layer for NVIDIA Jetson TX1/TX2/AGX Xavier/Nano -====================================================================== - -Boards supported: -* Jetson-TX1 development kit (Linux4Tegra R32.3.1, JetPack 4.3) -* Jetson-TX2 development kit (Linux4Tegra R32.3.1, JetPack 4.3) -* Jetson AGX Xavier development kit (Linux4Tegra R32.3.1, JetPack 4.3) -* Jetson Nano development kit (Linux4Tegra R32.3.1, JetPack 4.3) - -Also supported thanks to community support: -* Jetson-TX2i module (Linux4Tegra R32.3.1, JetPack 4.3) -* Jetson-TX2 4GB module (Linux4Tegra R32.3.1, JetPack 4.3) -* Jetson AGX Xavier 8GB module (Linux4Tegra R32.3.1, JetPack 4.3) - - -This layer depends on: -URI: git://git.openembedded.org/openembedded-core -branch: master -LAYERSERIES_COMPAT: zeus - - -PLEASE NOTE ------------ - -* Starting with JetPack 4.2, packages outside the L4T BSP can - only be downloaded with an NVIDIA Developer Network login. - So to use CUDA 10, cuDNN, and any other packages that require - a Devnet login, you **must** create a Devnet account and - download the JetPack packages you need for your builds using - NVIDIA SDK Manager. - - You must then set the variable NVIDIA_DEVNET_MIRROR to - "file://path/to/the/downloads" in your build configuration - (e.g., local.conf) to make them available to your bitbake - builds. This can be the NVIDIA SDK Manager downloads - directory, `/home/$USER/Downloads/nvidia/sdkm_downloads` - - **Note** Starting with L4T R32.3.1 and JetPack 4.3, The Tegra - Multimedia API kit has moved to JetPack, so **all builds** - now require you to set up an SDK Manager downloads area. - -* The SDK Manager downloads a different package of CUDA host-side - tools depending on whether you are running Ubuntu 16.04 - or 18.04. If you downloaded the Ubuntu 16.04 package, you - should add - - CUDA_BINARIES_NATIVE = "cuda-binaries-ubuntu1604-native" - - to your build configuration so the CUDA recipes can find - them. Otherwise, the recipes will default to looking for - the Ubuntu 18.04 package. - -* The TensorRT 6.0.1 packages for Xavier are different from - those for TX1/TX2, even though the deb files have the same - name. To prevent mixups during the build, the recipe here - expects to find the Xavier packages in a `DLA` subdirectory - under `${NVIDIA_DEVNET_MIRROR}`, and non-Xavier packages - in a `NoDLA` subdirectory. - - If you need to include TensorRT in your builds, you **must** - create the subdirectory and move all of the TensorRT packages - downloaded by the SDK Manager there. Xavier example: - - $ cd ~/Downloads/nvidia/sdkm_downloads - $ mkdir DLA - $ mv tensorrt*.deb libnvinfer*.deb DLA/ - -* CUDA 10 supports up through gcc 7 only, and some NVIDIA-provided - binary libraries appear to be compiled with g++ 7 and cause linker - failures when building applications with g++ 6, so **only** gcc 7 - should be used if you intend to use CUDA. See the following wiki - pages for instructions on including gcc 7 in your builds: - - [Using gcc7 from the contrib layer](https://github.com/madisongh/meta-tegra/wiki/Using-gcc7-from-the-contrib-layer) - [Using linaro gcc7 for CUDA support](https://github.com/madisongh/meta-tegra/wiki/Using-linaro-gcc7-for-CUDA-support) - - -Contributing ------------- - -Please use GitHub (https://github.com/madisongh/meta-tegra) to submit -issues or pull requests, or add to the documentation on the wiki. -Contributions are welcome! diff --git a/README b/README new file mode 120000 index 00000000..42061c01 --- /dev/null +++ b/README @@ -0,0 +1 @@ +README.md \ No newline at end of file diff --git a/README.md b/README.md deleted file mode 120000 index 100b9382..00000000 --- a/README.md +++ /dev/null @@ -1 +0,0 @@ -README \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 00000000..28347e63 --- /dev/null +++ b/README.md @@ -0,0 +1,83 @@ +OpenEmbedded/Yocto BSP layer for NVIDIA Jetson TX1/TX2/AGX Xavier/Nano +====================================================================== + +Boards supported: +* Jetson-TX1 development kit (Linux4Tegra R32.3.1, JetPack 4.3) +* Jetson-TX2 development kit (Linux4Tegra R32.3.1, JetPack 4.3) +* Jetson AGX Xavier development kit (Linux4Tegra R32.3.1, JetPack 4.3) +* Jetson Nano development kit (Linux4Tegra R32.3.1, JetPack 4.3) + +Also supported thanks to community support: +* Jetson-TX2i module (Linux4Tegra R32.3.1, JetPack 4.3) +* Jetson-TX2 4GB module (Linux4Tegra R32.3.1, JetPack 4.3) +* Jetson AGX Xavier 8GB module (Linux4Tegra R32.3.1, JetPack 4.3) + + +This layer depends on: +URI: git://git.openembedded.org/openembedded-core +branch: master +LAYERSERIES_COMPAT: zeus + + +PLEASE NOTE +----------- + +* Starting with JetPack 4.2, packages outside the L4T BSP can + only be downloaded with an NVIDIA Developer Network login. + So to use CUDA 10, cuDNN, and any other packages that require + a Devnet login, you **must** create a Devnet account and + download the JetPack packages you need for your builds using + NVIDIA SDK Manager. + + You must then set the variable NVIDIA_DEVNET_MIRROR to + "file://path/to/the/downloads" in your build configuration + (e.g., local.conf) to make them available to your bitbake + builds. This can be the NVIDIA SDK Manager downloads + directory, `/home/$USER/Downloads/nvidia/sdkm_downloads` + + **Note** Starting with L4T R32.3.1 and JetPack 4.3, The Tegra + Multimedia API kit has moved to JetPack, so **all builds** + now require you to set up an SDK Manager downloads area. + +* The SDK Manager downloads a different package of CUDA host-side + tools depending on whether you are running Ubuntu 16.04 + or 18.04. If you downloaded the Ubuntu 16.04 package, you + should add + + CUDA_BINARIES_NATIVE = "cuda-binaries-ubuntu1604-native" + + to your build configuration so the CUDA recipes can find + them. Otherwise, the recipes will default to looking for + the Ubuntu 18.04 package. + +* The TensorRT 6.0.1 packages for Xavier are different from + those for TX1/TX2, even though the deb files have the same + name. To prevent mixups during the build, the recipe here + expects to find the Xavier packages in a `DLA` subdirectory + under `${NVIDIA_DEVNET_MIRROR}`, and non-Xavier packages + in a `NoDLA` subdirectory. + + If you need to include TensorRT in your builds, you **must** + create the subdirectory and move all of the TensorRT packages + downloaded by the SDK Manager there. Xavier example: + + $ cd ~/Downloads/nvidia/sdkm_downloads + $ mkdir DLA + $ mv tensorrt*.deb libnvinfer*.deb DLA/ + +* CUDA 10 supports up through gcc 7 only, and some NVIDIA-provided + binary libraries appear to be compiled with g++ 7 and cause linker + failures when building applications with g++ 6, so **only** gcc 7 + should be used if you intend to use CUDA. See the following wiki + pages for instructions on including gcc 7 in your builds: + + [Using gcc7 from the contrib layer](https://github.com/madisongh/meta-tegra/wiki/Using-gcc7-from-the-contrib-layer) + [Using linaro gcc7 for CUDA support](https://github.com/madisongh/meta-tegra/wiki/Using-linaro-gcc7-for-CUDA-support) + + +Contributing +------------ + +Please use GitHub (https://github.com/madisongh/meta-tegra) to submit +issues or pull requests, or add to the documentation on the wiki. +Contributions are welcome!