GH-48582: [CI][GPU][C++][Python] Add new CUDA jobs using the new self-hosted runners

[raulcd]

Rationale for this change

The CUDA jobs stopped working when Voltron Data infrastructure went down. We have set up with ASF Infra a runs-on solution to run CUDA runners.

What changes are included in this PR?

Add the new workflow for cuda_extra.yml with CI jobs that use the runs-on CUDA runners.

Due to the underlying instances having CUDA 12.9 the jobs to be run are:

• AMD64 Ubuntu 22 CUDA 11.7.1
• AMD64 Ubuntu 24 CUDA 12.9.0
• AMD64 Ubuntu 22 CUDA 11.7.1 Python
• AMD64 Ubuntu 24 CUDA 12.9.0 Python

A follow up issue has been created to add jobs for CUDA 13, see: #48783

A new label CI: Extra: CUDA has also been created.

Are these changes tested?

Yes via CI

Are there any user-facing changes?

No

• GitHub Issue: [CI][GPU][C++][Python] Add new jobs for cuda #48582

[github-actions]

⚠️ GitHub issue #48582 has been automatically assigned in GitHub to PR creator.

[raulcd]

@pitrou @kou this PR was originally created to test the runs-on solution using our AWS infra to add the CUDA runners.
We used to have 4 CI jobs:

• CUDA 13.0.2 C++
• CUDA 13.0.2 Python
• CUDA 11.7.1 C++
• CUDA 11.7.1 Python

From an organization standpoint would you prefer to have the C++ jobs added to the CI: Extra: C++ and create a new CI: Extra: Python or should we add a new CI: Extra: Cuda with those 4 jobs?

[raulcd]

The Python CUDA 13.0.2 errors are not related to this PR per se (this is only adding the new runners) but there seems to be an issue initializing CUDA:
OSError: Cuda error 999 in function 'cuInit': [CUDA_ERROR_UNKNOWN] unknown error
@gmarkall @pitrou should I create a new issue to fix this separately once we have added the new runners or do you have any pointers for a fix?

[gmarkall]

do you have any pointers for a fix?

Perhaps the driver version on the machine is older than 13.0.2 used in the container. Do you have a way to check the driver version installed on the machine that's hosting the docker image? (e.g. what is its nvidia-smi output?)

[gmarkall]

From the nvidia-smi output:

| NVIDIA-SMI 575.57.08              Driver Version: 575.57.08      CUDA Version: 12.9     |

I think that the machine will need at least driver version 580 for a CUDA 13 container. Are you able to change the underlying machine?

[gmarkall]

Alternatively, it may be possible to make this configuration work by adding the relevant cuda-compat package to the container, which I think from https://docs.nvidia.com/deploy/cuda-compatibility/forward-compatibility.html#id1 may be cuda-compat-13-0.

[raulcd]

We are using the default images built here (yes they point out they have cuda 12):
https://github.com/runs-on/runner-images-for-aws?tab=readme-ov-file#gpu
There's the possibility of creating our own AWS images with packer but I am unsure we want to follow that route due to maintenance overhead:
https://runs-on.com/runners/gpu/#using-nvidia-deep-learning-amis
I have a meeting with Cyril from runs-on tomorrow, I might ask if CUDA 13 is in their roadmap.
Maybe we should go with cuda-compat here, I am trying a naive approach for testing purposes at the moment

[raulcd]

Thanks @gmarkall for your help, unfortunately it seems to fail with a different error if cuda-compat-13-0 is installed:

 cuda.core._utils.cuda_utils.CUDAError: CUDA_ERROR_INVALID_IMAGE: This indicates that the device kernel image is invalid. This can also indicate an invalid CUDA module.

and nvidia-smi now shows 13.0:

+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 575.57.08              Driver Version: 575.57.08      CUDA Version: 13.0     |
|-----------------------------------------+------------------------+----------------------+

[kou]

I prefer CI: Extra: CUDA because CUDA isn't related in most changes. If we use CI: Extra: C++/Python, we need to use CUDA runners for many non CUDA related changes.

[raulcd]

I plan to merge this to have CUDA runners later today. @pitrou @kou in case you want to take a look before that.

[kou]

+1

[raulcd]

I've simplified the job adding cuda and ubuntu to the matrix. Thanks @kou I'll merge this into 23.0.0 in case we do a patch release in the future to have cuda validation.

[conbench-apache-arrow]

After merging your PR, Conbench analyzed the 3 benchmarking runs that have been run so far on merge-commit 985b16e.

There weren't enough matching historic benchmark results to make a call on whether there were regressions.

The full Conbench report has more details.