I am here for some advice concerning the best way to set up my Jetson Xavier NX.
My goal is to gain skills in computer vision using multiple cameras and in this way I recently bought this board
However, I was surprised to find there is no additional storage (on the carrier board) than the 16GB of the module and no nVME or SD card connectors.
I got 14.7GB of available space on / and after removing some default libraries I get 4.4GB of remaining space.
It is not enough and I would install many libraries to work with like CUDA
So I have in mind 2 main solutions using an external storage drive :
- Set up docker environment on the external drive, creating a container and installing all the libraries in the volume attached.
- Change the default location of user packages to the external drive.
Question (1) : Concerning the 2nd solution, is it possible that my future programmes will run slower because of the time to access libraries on the external storage ?
In my mind using the 1st one seems to be more practical : working in a predefinite workspace and everything is located at the same place. I just have to start the container.
I tried implementing the 1st solution :
- Fixing the mount point for my external drive to /media/nvidia
- Editing /etc/docker/daemon.json to set up docker’s root directory to /media/nvidia/docker + adding default_runtime to nvidia-container-runtime
- Following dusty_nv’s jetson-container to build the ML container
But when it comes to this 3rd step, I got an error due to libcurand.so.10 not found.
So here are my Questions (2) : What are your opinion about these 2 solutions ? Do am I doing right ? Do you have better ones ? Should I use another base image ?
Thank you for help.