Docker for fast.ai


(Kai Lichtenberg) #21

@tthrift Hmm, I’m pretty sure, that the XServer should not be a big slow down. When I view the GPU usage with watch nvidia-smi I’m seeing around 50 %.


#22

Nvidia recently released Ubuntu 18.04 with CUDA 9.2 images on dockerhub, anyone tried upgrading their images to it? Is it worth it, any fast.ai code that breaks with upgrade?


(Kai Lichtenberg) #23

@xev In this image I’m using the images from their NGC registry. They have a monthly release cycle and in the May release uses 16.04. Maybe they switch to 18.04 in the June release.


#24

Well I meant these images - https://hub.docker.com/r/nvidia/cuda/ - they already released 9.2-cudnn7-*-ubuntu18.04. Worth the trouble upgrading over ubuntu 16.04 image?


(Kai Lichtenberg) #25

@xev Ahh, sorry I thought I’m in my own Dockerfile thread. Personally I don’t think it’s giving you any advantage running the same CUDA/CuDNN stack on 16.04 or 18.04.