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)
Running
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?
Cheers