Im trying to run CUDA 10.1. on the fluidsGL sample, but I always get this error:
CUDA error at fluidsGL.cpp:472 code=999(cudaErrorUnknown) "cudaGraphicsGLRegisterBuffer(&cuda_vbo_resource, vbo, cudaGraphicsMapFlagsNone)"
I’ve got a Thinkpad T480s Laptop running 20.04. with dedicated Nvidia MX150 and onboard Intel UHD 620. Because of the dual-graphics (I want Intel running the display and Nvidia running heavy programs; I do this with off-loading), I figured it would be best to install CUDA 10.1. from the
.run-file. So I followed the installation steps, and if I want to verify the installation with the sample run, I get the above error.
Too often I had either other errors, workarounds and glitches etc. that left me doing a timeshift and redoing the whole installation. Then I saw that people just use
sudo apt-get install nvidia-cuda-toolkit to install CUDA, which I then did too. Typing
nvcc -V did give me the correct CUDA version.
But then making one of the samples above errored with
make: /usr/local/cuda/bin/nvcc: command not found.
I figured with
which nvcc that it nvcc was instead installed in
/usr/bin/nvcc, so, naively, I created a softlink:
sudo ln -s /usr/bin/nvcc /usr/local/cuda/bin/nvcc
This indeed left me making the sample error-free (after having installed
freeglut3, since the error
/usr/bin/ld: -lglut could not be found; collect2: error: ld returned 1 exit status! occured)
import torch torch.cuda.is_available()
in a ipynb-cell results in
True, which leaves me thinking, CUDA works.
However, running the fluidGL example gives still gives me the above
code=999(cudaErrorUnknown)-error. Making works.
Was this even feasible, what I all did? Or is there something I missed.
How can I solve the error?