Streamlining NVIDIA Driver Deployment on RHEL 8 with Modularity Streams

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NVIDIA GPUs have become mainstream for accelerating a variety of workloads from machine learning, high-performance computing (HPC), content creation workflows, and data center applications. For these enterprise use cases, NVIDIA provides a software stack powered by the CUDA platform: drivers, CUDA-X acceleration libraries, CUDA-optimized applications, and frameworks. Deploying the NVIDIA driver is one of the…

Hi this is Kevin, hope you’ve enjoyed reading my blog post. Be sure to check out my presentations on this subject, at NVIDIA GTC Fall 2020 and Red Hat Summit 2020. On a related note, the yum-packaging-precompiled-kmod repository on GitHub, has a detailed README and pull requests are welcome. Shout out to our friends at Red Hat, that collaborated on this project. Finally, if you have any questions or comments, please let us know.


thanks for the guide. However, are you aware that these drivers have not worked since RHEL 8.3 came out, for few months? Any plans to fix the build?

Hi @ilkka.tengvall_nv could you expand on “drivers have not worked”? Please fill in the blanks:

  1. NVIDIA driver version:
  2. RHEL kernel version:
  3. modularity stream:
  4. modularity profile: <default, ks, fm>

I have confirmed that the precompiled driver packages are functional on RHEL 8.3, with two exceptions

  • 418 driver (a fix is coming soon)
  • kernel 4.18.0-240.1.1 and newer (4.18.0-240 from the RHEL 8.3 ISO image was released on the same day and thus skipped over)

Also feel free to report such issues here:

Thanks, I’m not at the computer now, but I have some older posts here describing the problem:

I’ve had troubles with it for long.

By the way, I’ve added this page: RHEL8 precompiled to the repository, that includes a table of available NVIDIA kernel module packages.