I’ve read multiple times that CUDA dominates, mostly because NVIDIA dominates. Rocm is the AMD equivalent, but OpenCL also exists. From my understanding, these are technologies used to program graphics cards - always thought that shaders were used for that.
There is a huge gap in my knowledge and understanding about this, so I’d appreciate somebody laying this out for me. I could ask an LLM and be misguided, but I’d rather not 🤣
This cannot be right. I’m pretty sure that it is possible to run OpenCL applications in containers that are sharing a GPU.
I should test this if I have time. My plan was to use a distrobox container since that shares the GPU by default and run something like lc0 to see if opencl acceleration works.
Now where is my remindme bot? (I won’t have time).
You really piqued my interest. I use docker/podman.
W/ an AMD graphics card, eglinfo on the host shows the card is AMD Radeon and driver is matching that.
In the container, without --gpus=all, it shows the card is unknown and the driver is “swrast” (so just CPU fallback).
To make --gpus=all work, it gives the error
I was doing a bad job searching before. I found that AMD can share the GPU, it just works a little differently in terms of how to launch the container. https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/amdgpu-install.html#amdgpu-install-dkms
But sadly my AMD GPU is too old/junk to have current driver support.
Anyways, appreciate the reply! Now I can mod my code to run on cheaper cloud instances.
(Note I’m an OpenGL/3D app developer, but probably OpenCL works about the same architecturally)