Install DEM-Engine

Installation from source

On a Linux machine, install CUDA if you do not already have it. Useful installation instructions may be found here.

Some additional troubleshooting tips for getting CUDA ready:

• On WSL this code may be buildable (and this is the guide for installing CUDA on WSL), but may not run. This is due to the many limitations on unified memory and pinned memory support on WSL. A native Linux machine or cluster is recommended.

Once CUDA is ready, clone this project and then:

git submodule init
git submodule update

This will pull the submodule NVIDIA/jitify so that we can do runtime compilation.

Then, one typical choice is to make a build directory in it. Then in the build directory, use cmake to configure the compilation. An example:

mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..

You may want to use this information if you need to update cmake to the newest.

We suggest that you install a cmake GUI such as ccmake, and ninja_build generator, to better help you configure the project. In this case, the example above can be done like this alternatively:

mkdir build
cd build
ccmake -G Ninja ..

You generally do not have to change the build options in the GUI, but preferably you can change CMAKE_BUILD_TYPE to Release, and if you need to install this package as a library you can specify a CMAKE_INSTALL_PREFIX.

Some additional troubleshooting tips for generating the project:

• If some dependencies such as CUB are not found, then you probably need to manually set $PATH and $LD_LIBRARY_PATH. An example is given below for a specific version of CUDA, note it may be different on your machine or cluster. You should also inspect if nvidia-smi and nvcc --version give correct returns.

  export CPATH=/usr/local/cuda-12.0/targets/x86_64-linux/include${CPATH:+:${CPATH}}
  export PATH=/usr/local/cuda-12.0/bin${PATH:+:${PATH}}
  export PATH=/usr/local/cuda-12.0/lib64/cmake${PATH:+:${PATH}}
  export LD_LIBRARY_PATH=/usr/local/cuda-12.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
  export CUDA_HOME=/usr/local/cuda-12.0

Finally, build the project.

ninja

Some additional troubleshooting tips for building the project:

• If you see some grammatical errors during compilation, such as filesystem not being a member of std or arguments not expanded with ..., then manually setting the flag TargetCXXStandard to STD_CXX17 might help.

Install as C++ library

Set the CMAKE_INSTALL_PREFIX flag in cmake GUI to your desired installation path and then

ninja install

We provide examples of linking against both Chrono and DEME for co-simulations in chrono-projects.

Assuming you know how to build chrono-projects linking against a Chrono installation, then the extra things that you should do to link against DEME are

• Set ENABLE_DEME_TESTS to ON;
• Set ChPF_DIR when prompted. It should be in <your_install_dir>/lib64/cmake/ChPF;
• Set DEME_DIR when prompted. It should be in <your_install_dir>/lib64/cmake/DEME.

Then build the project and you should be able to run the demo scripts that demonstrate the co-simulation between DEME and Chrono.