Fastai on AMD GPUs - Working dockerfile

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!

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@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?

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.

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.