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ERROR: failed checking for nvcc. #46
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I am not sure what is the issue but if you are unable to find nvcc then possibly you are missing cuda toolkit installation. you can follow this cuda installlation guide - https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html |
I think you are not correct @mdoijade. Although cuda is installed:
I get an error when want to build ffmpeg with nvenc:
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Hi, the same goes for me on two machines. One Ubuntu 18.04, second Ubuntu 20.10. Cuda toolkit 11.1 drivers 455.45.
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After altering n |
@Tony763 where do you alter the nvccflags_default ? |
Hi @swissbeats93:
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I don't see what you altered it to @Tony763, also doesn't the presence of cuda say that you have cuvid present? |
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I saw it now. This is the page: https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html . I went with 75 because I'm on Turing architecture |
@swissbeats93 is it wotking for You?
Nvidia verification is OK - url |
@Tony763 It's working for me. Did you restart the system? |
This is what I did.
After that I restarted, I find that ffmpeg is installed to /usr/local (the cuda stuff) and $HOME/bin for the remainder |
When I tried to compile with cuda support I got `nvcc fatal : Unsupported gpu architecture 'compute_30'` I googled that and found this issue - NVIDIA/cuda-samples#46 - where they suggested changing it to `nvccflags_default="-gencode arch=compute_75,code=sm_75 -O2` I wanted to try making it work for multiple versions - I found this webpage - https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/ that listed flags for max compatibility
https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/ This website may help to find which nvccflags_default to use. |
for those who are lurking, you can just add |
Weird! inside docker ffmpeg configured without adding nvccflags but on the host i have to add _75. docker container got cuda-10 while host is of cuda-11. same issue with container with cuda-10. |
Not running ./configure with sudo worked for me |
For people with problem with NVCC, try to check if CUDA is installed properly. Also, seems like nvcc is not in path, but if you look at /usr/local/cuda/bin you can find the binaries related to the Nvidia CUDA Compiler (nvcc). So, in my Ubuntu 20.04: export PATH=$PATH:/usr/local/cuda/bin solved the problem. |
Still had this issue in Ubuntu-based Pop!_OS 22.04, had done everything else and finally adding the directory to path as @caio-vinicius got it working. |
NVCC may actually be installed correctly, you just need to make sure that your GCC version is < 10. If you check in the error logs, it says that versions gcc greater than 10 are not supported, but the console logged error message is that nvcc is not installed! To fix this: Note that this is a common trend where applications report an unrelated error while the underlying error is the wrong gcc version. If you encounter mysterious errors in the future, one of the first things you should do is switch to a higher gcc version! |
For the sake of posterity, using lmod, I solved it by getting GCC to be compatible with the loaded CUDA: module load system/CUDA/11.8.0 |
Hi. My error was due to an incompatible version of gcc. To solve I add to add -ccbin clang-14 to the nvccflags: |
System information (version)
Detailed description
I follow this instruction to install ffmpeg. But it fail to check nvcc.
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