AutoPas is a free and open-source library written in C++ providing multiple efficient algorithms for particle simulations. In order to fully exploit modern processors, it is necessary to distribute the computational load evenly among multiple threads. One of the shared-memory parallelization approaches implemented in AutoPas cuts the simulation domain into multiple equally large slices and assigns one slice to each thread. However, for inhomogeneous particle distributions, this does not distribute the computational load equally among the threads.

In this thesis, multiple variants of sliced traversal for different particle containers were implemented, which aid in balancing the computational load among the threads. The new traversals were benchmarked using two different particle simulations, which were run on the Haswell architecture based CoolMUC-2 cluster. The results show that each of the new traversal options outperforms the original unbalanced sliced traversal for the same container for at least one scenario. As AutoPas uses autotuning to determine the best traversal for the scenario, this results in an absolute improvement.

Keywords: AutoPas, Load Balancing, Molecular Dynamics