Molecular dynamics simulations allow for the approximation of particle movements using numerical methods. Often, 2-body potentials are used for this, but the accuracy achieved is insufficient in more specific scenarios, which is why 3-body potentials, such as the Axilrod-Teller potential, can also be calculated.

However, this can only be achieved with significantly higher computational effort, as the computational cost of 3-body potentials grows cubically with the number of particles, and molecular dynamics often involves millions of particles. Therefore, it is crucial to use the most efficient algorithms for force calculation depending on the composition of the simulation space.

AutoPas is a C++ library that enables auto-tuning of molecular dynamics simulations. To offer AutoPas more options for calculating 3-body potentials, we implement three new methods for traversing particle triplets based on the Verlet Cluster List algorithm and compare them with similar methods from the library that are based on the Linked Cells and Verlet Lists algorithms.

We find that the new traversal methods generally perform better in most scenarios than traversals using the Linked Cells algorithm, but they perform significantly worse when compared to similar methods based on the Verlet Lists algorithm. The force calculation during traversal seems to be inefficient with the AoS data layout, so any increase in the number of particles per cluster degrades the performance — except for the case of 2 particles per cluster in the List Intersection approach.

However, due to the generally better parallel efficiency, lower memory requirements, and the lower increase in runtime both for a higher cutoff and for higher particle density, the traversal has potential for larger simulations where the cluster structure might be utilized better.