In reply to @kupac:matrix.org
It's in experimental phase, so we don't have to rush with the packaging imo. You can file a bug report upstream about the suid and wait for it to run its course.

Could you please give me a bit more information? I added it to a shell.nix which seemed promising:

# Run with `nix-shell cuda-shell.nix`
# { pkgs ? import <nixpkgs> {} }:
with import <nixpkgs> {
  config = {
    allowUnfree = true;
    cudaSupport = true;
  };
};

pkgs.mkShell {
   name = "cuda-env-shell";
   buildInputs = with pkgs; [
     git gitRepo gnupg autoconf curl
     procps gnumake util-linux m4 gperf unzip
     cudatoolkit linuxPackages.nvidia_x11
     libGLU libGL
     xorg.libXi xorg.libXmu freeglut
     xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib 
     ncurses5 stdenv.cc binutils
     python39
     python39Packages.numpy
     python39Packages.numba
     libstdcxx5
     cudaPackages_11.cudatoolkit
   ];
   shellHook = ''
      export CUDA_PATH=${pkgs.cudatoolkit}
      # export LD_LIBRARY_PATH=${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib
      export EXTRA_LDFLAGS="-L/lib -L${pkgs.linuxPackages.nvidia_x11}/lib"
      export EXTRA_CCFLAGS="-I/usr/include"
      export LD_LIBRARY_PATH=${pkgs.cudaPackages_11.cudatoolkit}/lib:$LD_LIBRARY_PATH
      export NUMBAPRO_NVVM=${pkgs.cudaPackages_11.cudatoolkit}/nvvm/lib64/libnvvm.so
      export NUMBAPRO_LIBDEVICE=${pkgs.cudaPackages_11.cudatoolkit}/nvvm/libdevice
   '';          
}

so when I go into that shell, create a python virtualenv, go into it, install numba. And try to run:

from numba import cuda
print(cuda.detect())

It gives me:

Numba Version: 0.59.1
Traceback (most recent call last):
  File "/tmp/cuda/test.py", line 39, in <module>
    main()
  File "/tmp/cuda/test.py", line 19, in main
    print_version_info()
  File "/tmp/cuda/test.py", line 7, in print_version_info
    print("CUDA Version:", cuda.runtime.get_version())
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 111, in get_version
    self.cudaRuntimeGetVersion(ctypes.byref(rtver))
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 81, in safe_cuda_api_call
    self._check_error(fname, retcode)
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 89, in _check_error
    raise CudaRuntimeAPIError(retcode, msg)
numba.cuda.cudadrv.runtime.CudaRuntimeAPIError: [34] Call to cudaRuntimeGetVersion results in CUDA_ERROR_STUB_LIBRARY

I would not mind reading more, but I can't find good sources for nixos cuda support to jump off from. Thanks again.

In reply to @jeroenvb3:matrix.org

Could you please give me a bit more information? I added it to a shell.nix which seemed promising:

# Run with `nix-shell cuda-shell.nix`
# { pkgs ? import <nixpkgs> {} }:
with import <nixpkgs> {
  config = {
    allowUnfree = true;
    cudaSupport = true;
  };
};

pkgs.mkShell {
   name = "cuda-env-shell";
   buildInputs = with pkgs; [
     git gitRepo gnupg autoconf curl
     procps gnumake util-linux m4 gperf unzip
     cudatoolkit linuxPackages.nvidia_x11
     libGLU libGL
     xorg.libXi xorg.libXmu freeglut
     xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib 
     ncurses5 stdenv.cc binutils
     python39
     python39Packages.numpy
     python39Packages.numba
     libstdcxx5
     cudaPackages_11.cudatoolkit
   ];
   shellHook = ''
      export CUDA_PATH=${pkgs.cudatoolkit}
      # export LD_LIBRARY_PATH=${pkgs.linuxPackages.nvidia_x11}/lib:${pkgs.ncurses5}/lib
      export EXTRA_LDFLAGS="-L/lib -L${pkgs.linuxPackages.nvidia_x11}/lib"
      export EXTRA_CCFLAGS="-I/usr/include"
      export LD_LIBRARY_PATH=${pkgs.cudaPackages_11.cudatoolkit}/lib:$LD_LIBRARY_PATH
      export NUMBAPRO_NVVM=${pkgs.cudaPackages_11.cudatoolkit}/nvvm/lib64/libnvvm.so
      export NUMBAPRO_LIBDEVICE=${pkgs.cudaPackages_11.cudatoolkit}/nvvm/libdevice
   '';          
}

so when I go into that shell, create a python virtualenv, go into it, install numba. And try to run:

from numba import cuda
print(cuda.detect())

It gives me:

Numba Version: 0.59.1
Traceback (most recent call last):
  File "/tmp/cuda/test.py", line 39, in <module>
    main()
  File "/tmp/cuda/test.py", line 19, in main
    print_version_info()
  File "/tmp/cuda/test.py", line 7, in print_version_info
    print("CUDA Version:", cuda.runtime.get_version())
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 111, in get_version
    self.cudaRuntimeGetVersion(ctypes.byref(rtver))
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 81, in safe_cuda_api_call
    self._check_error(fname, retcode)
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/runtime.py", line 89, in _check_error
    raise CudaRuntimeAPIError(retcode, msg)
numba.cuda.cudadrv.runtime.CudaRuntimeAPIError: [34] Call to cudaRuntimeGetVersion results in CUDA_ERROR_STUB_LIBRARY

I would not mind reading more, but I can't find good sources for nixos cuda support to jump off from. Thanks again.

numba.cuda.cudadrv.runtime.CudaRuntimeAPIError: [34] Call to cudaRuntimeGetVersion results in CUDA_ERROR_STUB_LIBRARY

COmes from a symlink to the stub library in ${cudatoolkit}/lib/libcuda.so which you've listed in LD_LIBRARY_PATH and thus gave it a higher priority than the path to the real driver recorded in libraries' and executables' headers already

Thank you very much. The previously mentioned file does indeed run succesfully now. I did want to enable cudatoolkit I'm pretty sure. This is what I am now trying to get running:

from numba import cuda
import numpy as np

@cuda.jit
def cudakernel0(array):
    for i in range(array.size):
        array[i] += 0.5

array = np.array([0, 1], np.float32)
print('Initial array:', array)

print('Kernel launch: cudakernel0[1, 1](array)')
cudakernel0[1, 1](array)

print('Updated array:',array)

Which has this as the first error:

Initial array: [0. 1.]
Kernel launch: cudakernel0[1, 1](array)
/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/dispatcher.py:536: NumbaPerformanceWarning: Grid size 1 will likely result in GPU under-utilization due to low occupancy.
  warn(NumbaPerformanceWarning(msg))
Traceback (most recent call last):
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/nvvm.py", line 139, in __new__
    inst.driver = open_cudalib('nvvm')
  File "/nix/store/7m7c6crkdbzmzcrbwa4l4jqgnwj8m92b-python3.9-numba-0.59.1/lib/python3.9/site-packages/numba/cuda/cudadrv/libs.py", line 64, in open_cudalib
    return ctypes.CDLL(path)
  File "/nix/store/2j0l3b15gas78h9akrsfyx79q02i46hc-python3-3.9.19/lib/python3.9/ctypes/__init__.py", line 374, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: libnvvm.so: cannot open shared object file: No such file or directory

However, I do have the related env vars set:

[nix-shell:/tmp/cuda]$ echo $NUMBAPRO_NVVM
/nix/store/0c8nf26hx9x9jxgj0s9bq10xg75nbfv0-cuda-merged-12.2/nvvm/lib64/libnvvm.so

[nix-shell:/tmp/cuda]$ echo $NUMBAPRO_LIBDEVICE
/nix/store/0c8nf26hx9x9jxgj0s9bq10xg75nbfv0-cuda-merged-12.2/nvvm/libdevice

A stackoverflow says those are outdated and CUDA_HOME needs to be set. I do set it to the same as CUDA_PATH, but it doesn't seem to help. http://numba.pydata.org/numba-doc/latest/cuda/overview.html#setting-cuda-installation-path talks about ignoring minor version paths, but I don't think that is when I directly set it. I also don't have any non-minor version paths in /nix/store/

This is now my shell.nix:

with import <nixpkgs> {
  config = {
    allowUnfree = true;
    cudaSupport = true;
  };
};

pkgs.mkShell {
   name = "cuda-env-shell";
   buildInputs = [
     git gitRepo gnupg autoconf curl
     procps gnumake util-linux m4 gperf unzip
     libGLU libGL
     xorg.libXi xorg.libXmu freeglut
     xorg.libXext xorg.libX11 xorg.libXv xorg.libXrandr zlib 
     ncurses5 stdenv.cc binutils
     python39
     python39Packages.numpy
     python39Packages.numba
     libstdcxx5
     cudaPackages.cudatoolkit
   ];
   shellHook = ''
      export CUDA_PATH=${pkgs.cudaPackages.cudatoolkit}
      export CUDA_HOME=${pkgs.cudatoolkit}
      export EXTRA_CCFLAGS="-I/usr/include"
      export NUMBAPRO_NVVM=${pkgs.cudatoolkit}/nvvm/lib64/libnvvm.so
      export NUMBAPRO_LIBDEVICE=${pkgs.cudatoolkit}/nvvm/libdevice
   '';          
}

I'm sorry if its a lot to ask, but I would really like to learn about this and get it working. Do you see anything wrong with my stuff still?