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/1eddcf9a-ec4e-4764-8c40-61c749af6a0en%40googlegroups.com.
