Hi Yves,, I don't see a big problem here. The -arch option is suspicious, since it should be *compute_XX*, like *compute_80*, to specify a compute capability. But why it appears not detected or how it interacts with using Jupyter, I do not know, since I don't use it.
If it's about that your device is not detected while using Jupyter, then I don't know if I can reproduce that. I can have a try, but unable to guarantee. I would suggest that you try if you can run any other CUDA-based packages using Jupyter. BTW I don't know why trimesh could have this problem and it's weird. Ruochun On Friday, March 22, 2024 at 10:04:22 PM UTC+8 [email protected] wrote: > Hi Ruochun, > > It is quite difficult to install the tool given the cuda version to use. I > made it after trying several combinations for a long time. > The following is a script I made to install on Ubuntu 22.04 and my type of > graphic cards (on a fresh instance): > > #!/bin/bash > > # Remove old versions of CUDA and NVIDIA tools > sudo apt-get --purge remove -y "cublas*" "cuda*" "nvidia*" > sudo rm -rf /usr/local/cuda* > sudo apt-get autoremove -y && sudo apt-get autoclean -y > > # Install necessary utilities and libraries > sudo apt-get update > sudo apt-get install -y g++ freeglut3-dev build-essential libx11-dev > libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev > > # Install new CUDA, version 12.0 (amd, Ubuntu 22.04) > wget > https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin > sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 > wget > https://developer.download.nvidia.com/compute/cuda/12.0.0/local_installers/cuda-repo-ubuntu2204-12-0-local_12.0.0-525.60.13-1_amd64.deb > sudo dpkg -i cuda-repo-ubuntu2204-12-0-local_12.0.0-525.60.13-1_amd64.deb > sudo cp /var/cuda-repo-ubuntu2204-12-0-local/cuda-*-keyring.gpg > /usr/share/keyrings/ > sudo apt-get update > sudo apt-get install -y cuda-12.0 > > # Update environment variables > echo 'export PATH=/usr/local/cuda-12.0/bin:$PATH' >> ~/.bashrc > echo 'export LD_LIBRARY_PATH=/usr/local/cuda-12.0/lib64:$LD_LIBRARY_PATH' > >> ~/.bashrc > > # Install Miniconda > wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh > bash Miniconda3-latest-Linux-x86_64.sh -b -p $HOME/miniconda > > # Initialize Conda for the shell > $HOME/miniconda/bin/conda init > echo 'export PATH="$HOME/miniconda/bin:$PATH"' >> ~/.bashrc > > # Activate conda environment > source $HOME/.bashrc > source $HOME/miniconda/bin/activate > > # Install conda environment and tools > conda create -y -n pyDEME python=3.11 > conda activate pyDEME > conda install -y cmake > pip3 install DEME > > # OPTIONAL: few tools I use > conda config --add channels conda-forge > conda install -y seaborn matplotlib numpy scipy trimesh paraview shapely > gmsh PyArrow > pip install gmsh > > echo "Installation completed. Please reboot your system to apply all > changes and for the CUDA installation to be fully operational." > > I am not sure what exactly I am missing, to be honest. > > Best regards, > Yves > On Friday, March 22, 2024 at 4:42:02 AM UTC-4 Ruochun Zhang wrote: > >> Hi Yves, >> >> If you say this also happens to other packages like trimesh which is >> fully CPU-based, then I suspect it's the C++ compiler version. C++11 is way >> too old for anything. You should try updating the compiler that you are >> using for the installation of all the packages so it supports newer >> standards, at least C++17. That is my best guess at this moment. >> >> Thank you, >> Ruochun >> >> On Wednesday, March 20, 2024 at 5:04:16 AM UTC+8 [email protected] >> wrote: >> >>> Hello, >>> >>> I would like to know how to run DEM-Engine within a Jupyter notebook. >>> Indeed, I obtain the following error: >>> >>> Compiler options: -diag-suppress=550 -diag-suppress=177 -arch=compute_ >>> -std=c++11 >>> Traceback (most recent call last): >>> File "/home/cloud/PBR_DEME/test.py", line 46, in <module> >>> S.Instance.Initialize() >>> RuntimeError: NVRTC error: NVRTC_ERROR_INVALID_OPTION >>> >>> I also face this- same issue when using the trimesh python module >>> outside of Jupyter. However, I would like to know what triggers that error >>> so that I will hopefully solve both issues. >>> >>> Thanks! >>> >> -- You received this message because you are subscribed to the Google Groups "ProjectChrono" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/projectchrono/26302c5d-e44b-4bd2-a80a-3a02afcbd975n%40googlegroups.com.
