A library of CUDA implementations of neighbor search algorithms. Currently, the compressed LBVH and uniform grid are implemented. For additional details, please refer to the following publications:


  • HOOMD-blue >= 2.4.1
  • CMake >= 2.8.0
  • A CUDA toolkit compatible with HOOMD-blue and an NVIDIA GPU with compute capability >= 3.5.


The neighbor library is intended to be compiled similarly to a HOOMD-blue plugin. First, you must install HOOMD-blue and its dependencies with CUDA enabled. Then, add your HOOMD-blue installation to your PYTHONPATH. The neighbor library should automatically find HOOMD-blue. From the current directory,

export PYTHONPATH=/path/to/hoomd/2.4.1
mkdir build && cd build
cmake ..

Set any CMake flags that are appropriate for your target architecture (e.g., CUDA_ARCH_LIST). Most options will have already been fixed by your HOOMD-blue installation. Then, simply compile and install,

make install

If you have difficulties with the CMake configuration, refer to the HOOMD-blue documentation for hints regarding compilation.

The following will be found in your installation:

  • bin: benchmark executables
  • include: header files for the neighbor library
  • lib: the neighbor library

Note that the neighbor library uses a fixed RPATH at installation. If you move your HOOMD-blue installation, you will need to recompile the library.


You can validate your installation using the included test suite. Make sure that you are on a machine that has at least one available GPU, and then run

make test

or a specific test using ctest.