Has anyone had success running through the Fastai tutorials on any Jetson boards?

What has your experience been with Getting your Jetson setup and configured?

My experience so far, is the ARM CPU architecture does not have as much development support as the x86 architecture. So it is sometimes challenging getting the setup just right.

With the Fastai course in mind, do you feel that that Nano has the sufficient resources to run through some decent model development, training, etc, working with legit data sets? (for dev, not prod)

  • The Nano has 4 gig of memory shared between the CPU and GPU
  • I installed an 8 gig Swap file (good for the CPU, but not applicable for the GPU)
  • I’m running headless, to conserve as much memory as possible

Another option is to go for the JETSON TX2 (8GB) MODULE.

The gearhead in me say’s - “Go for the TX2 man!” However, I already have the Nano and I’m hoping I could make it through Fastai’s 7 lesson’s with it, before I invest more dollars in hardware.

Very interested others thoughts and perspectives on this topic!


In my mind, the TX2 is the worst of both worlds. It’s not quite big enough, and not the latest generation.
The Nano is super affordable, but quite old and limited.
The Jetson Xavier AGX is reasonably modern and has a nice Carmel CPU and fast GPU and plenty of RAM. And the devkit is now more affordable than before.
If neither of those work, then use a mini-ATX Linux box with a real GPU.