cudaPackages.cuda_compat: ignore missing libs provided at runtime
cudaPackages.gpus: Jetson should never build by default
cudaPackages.flags: don't build Jetson capabilities by default
cudaPackages: re-introduce filter for pre-existing CUDA redist packages in overrides
cudaPackages: only recurseIntoAttrs for the latest of each major version
cudaPackages.nvccCompatabilities: use GCC 10 through CUDA 11.5 to avoid a GLIBC incompatability
cudaPackages.cutensor: acquire libcublas through cudatoolkit prior to 11.4
cudaPackages.cuda_compat: mark as broken on aarch64-linux if not targeting Jetson
cudaPackages.cutensor_1_4: fix build
cudaPackages: adjust use of autoPatchelfIgnoreMissingDeps
cudaPackages.cuda_nvprof: remove unecessary override to add addOpenGLRunpath
cudaPackages: use getExe' to avoid patchelf warning about missing meta.mainProgram
cudaPackages: fix evaluation with Nix 2.3
cudaPackages: fix platform detection for Jetson/non-Jetson aarch64-linux
python3Packages.tensorrt: mark as broken if required packages are missing
Note: evaluating the name of the derivation will fail if tensorrt is not present,
which is why we wrap the value in `lib.optionalString`.
cudaPackages.flags.getNixSystem: add guard based on jetsonTargets
cudaPackages.cudnn: use explicit path to patchelf
cudaPackages.tensorrt: use explicit path to patchelf
Remove old CUDA toolkits (and corresponding CuDNN versions).
- Not supported by upstream anymore.
- We do not use them in nixpkgs.
- We do not test or actively maintain them.
- Anything but ancient GPUs is supported by newer toolkits.
Fixes#107131.
Since CUDA is unfree, we won't actually use this when testing Nixpkgs
officially. But I want to include this as they are useful for users of
Nixpkgs trying to set up / debug a CUDA environment.
