Cuda is not installed on jetson nano tx2 kit

I have purchased TX2 development kit few days back. The pre-default Linux is already installed on the system.

sudo apt-cache show nvidia-jetpack

Package: nvidia-jetpack
Version: 4.3-b134
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-container-csv-cuda (= 10.0.326-1), libopencv-python (= 4.1.1-2-gd5a58aa75), libvisionworks-sfm-dev (= 0.90.4), libvisionworks-dev (=, libvisionworks-samples (=, libnvparsers6 (= 6.0.1-1+cuda10.0), libnvinfer-plugin6 (= 6.0.1-1+cuda10.0), libcudnn7-doc (=, libcudnn7-dev (=, libnvinfer-samples (= 6.0.1-1+cuda10.0), libnvinfer-bin (= 6.0.1-1+cuda10.0), nvidia-container-csv-cudnn (=, libvisionworks-tracking-dev (= 0.88.2), vpi-samples (= 0.1.0), tensorrt (=, libopencv (= 4.1.1-2-gd5a58aa75), libnvinfer-doc (= 6.0.1-1+cuda10.0), libnvparsers-dev (= 6.0.1-1+cuda10.0), libcudnn7 (=, libnvidia-container0 (= 0.9.0~beta.1), cuda-toolkit-10-0 (= 10.0.326-1), nvidia-container-csv-visionworks (=, graphsurgeon-tf (= 6.0.1-1+cuda10.0), libopencv-samples (= 4.1.1-2-gd5a58aa75), python-libnvinfer-dev (= 6.0.1-1+cuda10.0), libnvinfer-plugin-dev (= 6.0.1-1+cuda10.0), libvisionworks (=, nvidia-container-toolkit (= 1.0.1-1), libnvinfer-dev (= 6.0.1-1+cuda10.0), nvidia-l4t-jetson-multimedia-api (= 32.3.1-20191209230245), libopencv-dev (= 4.1.1-2-gd5a58aa75), vpi-dev (= 0.1.0), vpi (= 0.1.0), python3-libnvinfer (= 6.0.1-1+cuda10.0), python3-libnvinfer-dev (= 6.0.1-1+cuda10.0), opencv-licenses (= 4.1.1-2-gd5a58aa75), nvidia-container-csv-tensorrt (=, libnvinfer6 (= 6.0.1-1+cuda10.0), libnvonnxparsers-dev (= 6.0.1-1+cuda10.0), libnvonnxparsers6 (= 6.0.1-1+cuda10.0), uff-converter-tf (= 6.0.1-1+cuda10.0), nvidia-docker2 (= 2.2.0-1), libvisionworks-sfm (= 0.90.4), libnvidia-container-tools (= 0.9.0~beta.1), nvidia-container-runtime (= 3.1.0-1), python-libnvinfer (= 6.0.1-1+cuda10.0), libvisionworks-tracking (= 0.88.2)
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.3-b134_arm64.deb
Size: 29746
SHA256: 958c32d872e11fef50737f6f38f93dd2c737f5d68886cb964d3da63151405337
SHA1: 32aa5a29be86550fbe9f4c249f2640bdfce596cd
MD5sum: 2b2590855299af3030509e55d9135c2d
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

sudo apt-get install cuda
Reading package lists… Done
Building dependency tree
Reading state information… Done
E: Unable to locate package cuda


I am not able to find the cuda cudnn path and opencv path in the library. could you please help me on this?

As it is a fresh one. I would suggest you use nvidia sdk manager to upgrade your devkit first to 4.4.

Since jetpack 4.3 you may also do it via apt directly. (See Docs)

Inside those apt repos (or via sdkmanager) you may then install cuda or any other utils you desire.
You can also just install cuda and opencv to your target by just copying the jetpack 4.3 debs to your system. (Choose 4.3 in sdkmanager and skip flash or select download only).



sudo apt install nvidia-jetpack
Reading package lists… Done
Building dependency tree
Reading state information… Done
E: Unable to locate package nvidia-jetpack

See the above docs how to proceed.

Check if you have the nvidia repos enabled in your apt sources. Then after checking or enabling call sudo apt-get update to fetch the current package lists.

With apt-cache madison nvidia-jetpack you’ll get an nice overview of which versions are available and from where they will get pulled. As a cli-ui version for apt I can recommend `aptitude if you want to peek into the package structures a little bit. It most often gives you also good recommendations how to solve conflicts or insights why somethings fails in a quite readable manner.

If you are stuck and want a fresh start, just use the sdkmanager on your host computer to build a new fs image and flash it to the target.