Fastai on AMD GPUs - Working dockerfile

#1

Hey all,

Today I attempted to get fast.ai working on my AMD GPU at home. The result of this work is a docker image that anyone can use to replicate my setup. It provides fastai and a jupyter notebook with support for AMD GPU acceleration.


https://cloud.docker.com/repository/docker/briangorman/fastai_rocm

In theory, this setup should work on any modern Linux kernel with an appropriate CPU/GPU combo. No additional work needed other than running this docker image.

For example I used a Intel Haswell GPU and a Radeon 480 with Antergos Linux. So far I haven’t run into any issues, but I haven’t run all of the notebooks yet. If you are not usually a Linux user and you want to give this a whirl, I would recommend Antergos or Fedora, since they both usually have recent kernels.

I hope this is helpful to someone, and let me know if there are any problems with this setup.

Cheers!

7 Likes
[Hardware] AMD GPU support
#2

@bgorman Thanks for sharing this. Might give it a spin on my AMD GPU too.
How does the performance you see compare to a NVIDIA consumer GPU?

#3

Also thanks from my part. I got my RX 570 8GB working with fast.ai on Ubuntu Mate with the docker file. Additionally I had to make the changes described here


and here

for it to work. Strangely my CPU (Ryzen 2700X) seems to be bottlenecking at the moment, so maybe I missed something.
But the GPU is speeding things up measurably compared to CPU only.

#4

Has anyone had luck getting this working recently? There seems to be issues for some people where the host rocm software for rocm 2.10 and 3.0/3.1 fail/segfault/don’t work on the newer kernels (i.e. 5.0, 5.3 LTS) and the rock-dkms isn’t supported for these newer kernels.