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Latest revision as of 21:08, 17 June 2022

CUDA is the nvidia libs for GPU programming for accelerated matrix manipulation and a requisite for CUDNN, nvidias dedicated tensor core library.

Installation Guide (+ CUDNN)

Installing Nvidia CUDA is shit, to successfully install the full cuda sdk and cudnn on a modern gentoo box required a bit of patience, trial and error. So this short guide should help you avoid a repeat of past mistakes.

If you're running an older version of the gentoo kernel, or a legacy driver, be sure to have the driver installed, signed (for hardened users) and loaded, you may not get all the features of a modern dist, or parts of this tutorial may not apply. Use discretion.

I have not yet tried on a no-multilib system, so I cannot guarantee functionality or a successful compilation.

1. Make an nvidia developer account on the nvidia-developer portal.

2. Download the appropriate CUDNN binturd.tar.xz and copy to /var/cache/distfiles

3. You will need to change your compiler version to nvidia spec, which means an emerge <=gcc-11 (I went with gcc 10.3.1 as of the time of writing this.) Select with gcc-config.

4. Ensure you're using =nvidia-cuda-toolkit-11.5

5. update make.conf accept license var.

6. emerge nvidia-cuda-sdk, If you've already installed it, be sure to recompile with the correct gcc version.

7. Utilize the library; pytorch, tensorflow, etc.