I get a Jetson Nano module from my industrial computer supplier (adxxxxxxh) , Everything go well when I run my program in docker in a CPU environment. However, When I want to use cuda , I find some expected problem before I trying.
The free space of the computer I got is only about 7GB left (with os installed, but cuda is not yet installed ), and the cuda in sdk manager are about 4GB, and the docker cuda based image which Nvidia provided is about 2GB, that means I have nearly no space left to put my application program in.
I ask my supplier if they can level up the eMMC to 32GB but the supplier says according to the nvidiaās Jetson nano SoM, they can do nothing to change the eMMC.
Since cuda is almost the essential part to run the Jetson and put the program to the docker image is the recommend way to do the work. How do you guy actually put them together into the limited storage space?
Cuda should be already be in the default filesystem . The SDKmanager itself installs CUDA toolkit for your host PC. Could you share what method you used to flash the nano ?
You can verify using : apt list --installed | grep cuda
or ls /usr/local/cuda
(I think this computer should be Jetson Xavier but the supplier insisted this is nano.)
mic-710aix@ubuntu:~$ apt list --installed | grep cuda
WARNING: apt does not have a stable CLI interface. Use with caution in scripts.
cuda-repo-ubuntu1804-11-0-local/now 11.0.2-450.51.05-1 arm64 [installed,local]
nvidia-l4t-cuda/now 32.4.3-20200625213407 arm64 [installed,local]
mic-710aix@ubuntu:~$ ls /usr/local/cuda
ls: cannot access ā/usr/local/cudaā: No such file or directory
the nano was flashed by my computer supplier. Since they said they didnāt install cuda when they flashed due to the space issue, there should be no cuda.
I also run the sdk manager myself to take a look, I see that the cuda installation in the sdk manager is optional so I think it is not default . ( I also tried other Jetson serials modules before and they were also without cuda, but I cannot check now )
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
I got a real Jetson nano module computer for testing ( called mic-710ai ), I flash out anything and install anything from sdkmanager and run the auto-remove command. Now I see that I have about 5GB and seems the CUDA library is still there, Iāll see what I can do to run the cuda docker in these space.
However, Iām curious that why to bother to do that āinstall anything then remove the non-cuda programā. Why not just make it optional , I even donāt want to see your parking lot tracking demo .
Practically we cannot have that temporary space to install all the components then remove half of them since we still need to install some sensorsā drivers.