1. How to Install JetPack

Depending on your Jetson device, there are multiple ways to install JetPack.

1.1. SD Card Image

For NVIDIA Jetson Nano and Jetson Xavier NX developer kit users, the simplest JetPack installation method is to follow the steps at the respective Getting Started web page to download and write an image to your microSD card, then use it to boot the developer kit.

1.2. NVIDIA SDK Manager

NVIDIA SDK Manager supports JetPack installation on these Jetson products:

  • NVIDIA Jetson AGX Xavier series modules on a Jetson AGX Xavier Developer Kit carrier board

  • NVIDIA Jetson Xavier NX modules on a Jetson Xavier NX Developer Kit carrier board

  • NVIDIA Jetson Nano module on a Jetson Nano Developer Kit carrier board

  • NVIDIA Jetson TX2 series modules on a Jetson TX2 Developer Kit carrier board

  • NVIDIA Jetson TX1 on a Jetson TX1 or TX2 Developer Kit carrier board

A Linux host computer running Ubuntu Linux x64 version 18.04 or 16.04 is required to run SDK Manager. Detailed instructions can be found here:

https://docs.nvidia.com/sdk-manager/index.html

1.3. Package Management Tool

NVIDIA offers JetPack components as Debian packages.

1.3.1. Install JetPack

Assuming your Jetson developer kit has been flashed with and is running L4T 32.3.1 or higher, the following commands will install all other JetPack components that correspond to your version of L4T:

sudo apt update
sudo apt install nvidia-jetpack

To view individual Debian packages which are part of nvidia-jetpack metapackage, enter the command:

sudo apt show nvidia-jetpack

Refer to the NVIDIA Jetson Linux Developer Guide for details about L4T specific Debian packages.

If disk space is limited (for example, when using a 16GB microSD card with a Jetson Nano or Jetson Xavier NX developer kit), use these commands:

sudo apt update
apt depends nvidia-jetpack | awk '{print $2}' | xargs -I {} sudo apt install -y {}

1.3.2. Upgrade JetPack

Starting with JetPack 4.4, upgrading to the next JetPack release can be achieved using a package management tool like apt. Follow the below steps to perform the upgrade:

  1. First, upgrade L4T.

    Please refer to the section "To upgrade to a new point release" in the NVIDIA Jetson Linux Developer Guide if upgrading to a new point release; for example, upgrading from JetPack 4.4 to JetPack 4.4.1.

    Please refer to the section "To upgrade to a new minor release" in the NVIDIA Jetson Linux Developer Guide if upgrading to a new minor release; for example, upgrading from JetPack 4.4 to JetPack 4.5.

  2. Next, upgrade the other JetPack components.

    sudo apt install nvidia-jetpack

If disk space is limited (for example, when using a 16GB microSD card with a Jetson Nano or Jetson Xavier NX developer kit), follow these steps:

  1. Remove all JetPack compute components.

    If you are running JetPack 4.4, use the following command:

    sudo apt autoremove --purge nvidia-container-csv-cuda libopencv-python libvisionworks-sfm-dev libvisionworks-dev libvisionworks-samples libnvparsers6 libcudnn7-doc libcudnn7-dev libnvinfer-samples libnvinfer-bin nvidia-container-csv-cudnn libvisionworks-tracking-dev vpi-samples tensorrt libopencv libnvinfer-doc libnvparsers-dev libcudnn7 libnvidia-container0 cuda-toolkit-10-0 nvidia-container-csv-visionworks graphsurgeon-tf libopencv-samples python-libnvinfer-dev libnvinfer-plugin-dev libnvinfer-plugin6 nvidia-container-toolkit libnvinfer-dev libvisionworks libopencv-dev nvidia-l4t-jetson-multimedia-api vpi-dev vpi python3-libnvinfer python3-libnvinfer-dev opencv-licenses nvidia-container-csv-tensorrt libnvinfer6 libnvonnxparsers-dev libnvonnxparsers6 uff-converter-tf nvidia-docker2 libvisionworks-sfm libnvidia-container-tools nvidia-container-runtime python-libnvinfer libvisionworks-tracking

    If you are running JetPack 4.5, use the following command:

    sudo apt autoremove --purge nvidia-container-csv-cuda libopencv-python libvisionworks-sfm-dev libvisionworks-dev libvisionworks-samples libnvparsers7 libcudnn8-doc libcudnn8-dev libnvinfer-samples libnvinfer-bin nvidia-container-csv-cudnn libvisionworks-tracking-dev vpi-samples tensorrt libopencv libnvinfer-doc libnvparsers-dev libcudnn8 libnvidia-container0 cuda-toolkit-10-2 nvidia-container-csv-visionworks graphsurgeon-tf libopencv-samples python-libnvinfer-dev libnvinfer-plugin-dev libnvinfer-plugin7 nvidia-container-toolkit libnvinfer-dev libvisionworks libopencv-dev nvidia-l4t-jetson-multimedia-api vpi-dev vpi python3-libnvinfer python3-libnvinfer-dev opencv-licenses nvidia-container-csv-tensorrt libnvinfer7 libnvonnxparsers-dev libnvonnxparsers7 uff-converter-tf nvidia-docker2 libvisionworks-sfm libnvidia-container-tools nvidia-container-runtime python-libnvinfer libvisionworks-tracking
  2. If the current version of JetPack was installed using SDK Manager, remove the local repo. (The example shown below assumes you will upgrade from JetPack 4.3.)

    sudo apt purge cuda-repo-l4t-10-0-local-10.0.326 libvisionworks-repo libvisionworks-sfm-repo libvisionworks-tracking-repo
  3. Free up additional disk space.

    sudo apt clean
  4. Upgrade L4T by referring to the OTA section of the NVIDIA Jetson Linux Developer Guide.

  5. Install the new JetPack components.

    apt depends nvidia-jetpack | awk '{print $2}' | xargs -I {} sudo apt install -y {}

1.4. List of JetPack OTA Packages

Following is a list of JetPack OTA update packages for Jetson devices as of the time of JetPack 4.5. Please refer to the Jetson Linux Developer Guide for the list of L4T OTA packages.

Component Group Packages

CUDA Toolkit for L4T

cuda-command-line-tools-10-2

cuda-compiler-10-2

cuda-core-10-2

cuda-cudart-10-2

cuda-cudart-dev-10-2

cuda-cufft-10-2

cuda-cufft-dev-10-2

cuda-cuobjdump-10-2

cuda-cupti-10-2

cuda-cupti-dev-10-2

cuda-curand-10-2

cuda-curand-dev-10-2

cuda-cusolver-10-2

cuda-cusolver-dev-10-2

cuda-cusparse-10-2

cuda-cusparse-dev-10-2

cuda-documentation-10-2

cuda-driver-dev-10-2

cuda-gdb-10-2

cuda-gdb-src-10-2

cuda-libraries-10-2

cuda-libraries-dev-10-2

cuda-license-10-2

cuda-memcheck-10-2

cuda-minimal-build-10-2

cuda-misc-headers-10-2

cuda-npp-10-2

cuda-npp-dev-10-2

cuda-nvcc-10-2

cuda-nvdisasm-10-2

cuda-nvgraph-10-2

cuda-nvgraph-dev-10-2

cuda-nvml-dev-10-2

cuda-nvprof-10-2

cuda-nvprune-10-2

cuda-nvrtc-10-2

cuda-nvrtc-dev-10-2

cuda-nvtx-10-2

cuda-samples-10-2

cuda-toolkit-10-2

cuda-tools-10-2

libcublas-dev

libcublas10

cuDNN

libcudnn8

libcudnn8-dev

libcudnn8-doc

TensorRT

libnvinfer7

libnvinfer-dev

libnvinfer-plugin7

libnvinfer-plugin-dev

libnvonnxparsers7

libnvonnxparsers-dev

libnvparsers7

libnvparsers-dev

libnvinfer-bin

libnvinfer-doc

libnvinfer-samples

tensorrt

python-libnvinfer

python-libnvinfer-dev

python3-libnvinfer

python3-libnvinfer-dev

graphsurgeon-tf

uff-converter-tf

OpenCV

libopencv

libopencv-dev

opencv-licenses

libopencv-python

libopencv-samples

VisionWorks

libvisionworks

libvisionworks-dev

libvisionworks-samples

libvisionworks-sfm

libvisionworks-sfm-dev

libvisionworks-tracking

libvisionworks-tracking-dev  

VPI

vpi

vpi-dev

vpi-samples

NVIDIA container runtime with Docker integration

nvidia-container-csv-cuda

nvidia-container-csv-cudnn

nvidia-container-csv-tensorrt

nvidia-container-csv-visionworks  

libnvidia-container0

libnvidia-container-tools

nvidia-container-toolkit

nvidia-container-runtime

nvidia-docker2

Multimedia API

nvidia-l4t-jetson-multimedia-api

1.5. JetPack Debian Packages on Host

NVIDIA provides a group of Debian packages that add or update JetPack components on the host computer.

To prepare the host computer to install JetPack components, do the following steps:

  1. Enter the following command to install the public key of the x86_64 repository of the public APT server:

    $ sudo apt-key adv --fetch-key http://repo.download.nvidia.com/jetson/jetson-ota-public.asc
  2. Add the following x86_64 repository to the host system's source list.

    • For an Ubuntu 16.04 host:

      deb http://repo.download.nvidia.com/jetson/x86_64 xenial r32.4
    • For an Ubuntu 18.04 host:

      deb http://repo.download.nvidia.com/jetson/x86_64 bionic r32.4
  3. Enter the following command:

    $ sudo apt update
  4. Use apt to download and install the required packages.

    $ sudo apt-get install nsight-graphics-for-l4t cuda-toolkit-10-2 cuda-cross-aarch64-10-2 libopencv libopencv-dev opencv-licenses libopencv-python libopencv-samples libvisionworks libvisionworks-dev libvisionworks-samples libvisionworks-sfm libvisionworks-sfm-dev libvisionworks-tracking libvisionworks-tracking-dev vpi vpi-dev vpi-samples nsight-systems-2020.2.3

The following table lists JetPack components that you can install with apt, and the packages that contain them.

Component Group Packages

CUDA

cuda

cuda-10-2

cuda-command-line-tools-10-2

cuda-compat-10-2

cuda-compiler-10-2

cuda-core-10-2

cuda-cudart-10-2

cuda-cudart-dev-10-2

cuda-cufft-10-2

cuda-cufft-dev-10-2

cuda-cuobjdump-10-2

cuda-cupti-10-2

cuda-cupti-dev-10-2

cuda-curand-10-2

cuda-curand-dev-10-2

cuda-cusolver-10-2

cuda-cusolver-dev-10-2

cuda-cusparse-10-2

cuda-cusparse-dev-10-2

cuda-demo-suite-10-2

cuda-documentation-10-2

cuda-driver-dev-10-2

cuda-drivers

cuda-gdb-10-2

cuda-gdb-src-10-2

cuda-libraries-10-2

cuda-libraries-dev-10-2

cuda-license-10-2

cuda-memcheck-10-2

cuda-minimal-build-10-2

cuda-misc-headers-10-2

cuda-npp-10-2

cuda-npp-dev-10-2

cuda-nsight-10-2

cuda-nsight-compute-10-2

cuda-nsight-systems-10-2

cuda-nvcc-10-2

cuda-nvdisasm-10-2

cuda-nvgraph-10-2

cuda-nvgraph-dev-10-2

cuda-nvjpeg-10-2

cuda-nvjpeg-dev-10-2

cuda-nvml-dev-10-2

cuda-nvprof-10-2

cuda-nvprune-10-2

cuda-nvrtc-10-2

cuda-nvrtc-dev-10-2

cuda-nvtx-10-2

cuda-nvvp-10-2

cuda-runtime-10-2

cuda-samples-10-2

cuda-sanitizer-api-10-2

cuda-toolkit-10-2

cuda-tools-10-2

cuda-visual-tools-10-2

libcublas10

libcublas-dev

libnvidia-cfg1-440

libnvidia-common-440

libnvidia-compute-440

libnvidia-decode-440

libnvidia-encode-440

libnvidia-fbc1-440

libnvidia-gl-440

libnvidia-ifr1-440

libxnvctrl0

libxnvctrl-dev

nsight-compute-2019.5.0

nsight-systems-2019.5.2

nvidia-compute-utils-440

nvidia-dkms-440

nvidia-driver-440

nvidia-headless-440

nvidia-headless-no-dkms-440

nvidia-kernel-common-440

nvidia-kernel-source-440

nvidia-modprobe

nvidia-settings

nvidia-utils-440

xserver-xorg-video-nvidia-440

CUDA cross-compile package (host)

cuda-cross-aarch64

cuda-cross-aarch64-10-2

cuda-cudart-cross-aarch64-10-2

cuda-cufft-cross-aarch64-10-2

cuda-cupti-cross-aarch64-10-2

cuda-curand-cross-aarch64-10-2

cuda-cusolver-cross-aarch64-10-2

cuda-cusparse-cross-aarch64-10-2

cuda-driver-cross-aarch64-10-2

cuda-misc-headers-cross-aarch64-10-2  

cuda-npp-cross-aarch64-10-2

cuda-nsight-compute-addon-l4t-10-2

cuda-nvgraph-cross-aarch64-10-2

cuda-nvml-cross-aarch64-10-2

cuda-nvrtc-cross-aarch64-10-2

libcublas-cross-aarch64

nsight-compute-addon-l4t-2019.5.0

Computer Vision – VisionWorks (host)   

libvisionworks

libvisionworks-dev

libvisionworks-samples

libvisionworks-sfm

libvisionworks-sfm-dev

libvisionworks-tracking

libvisionworks-tracking-dev

Computer Vision – VPI (host)

vpi

vpi-dev

vpi-samples

Developer Tools

nsight-graphics-for-l4t

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