N ways to simulate short-range particle systems: Automated algorithm selection with the node-level library AutoPas.

AutoPas is an open-source C++ library delivering optimal node-level performance by providing the ideal algorithmic configuration for an arbitrary scenario in a given short-range particle simulation. It acts as a black-box container, internally implementing an extensive set of algorithms, parallelization strategies, and optimizations that are combined dynamically according to the state of the simulation via auto-tuning. This paper gives an overview of the high-level user perspective, as well as the internal view, covering the implemented techniques and features. The library is showcased by incorporating it into the codes LAMMPS and ls1 mardyn, and by investigating various applications. We further outline node-level shared-memory performance and scalability of our auto-tuning software which is comparable to LAMMPS. Program Title: AutoPas CPC Library link to program files: https://doi.org/10.17632/9kdb2p76hv.1 Developer's repository link: https://github.com/AutoPas/AutoPas Code Ocean capsule: https://codeocean.com/capsule/0391732 Licensing provisions: BSD 2-clause Programming language: C++17, CMake 3.14 Nature of problem: The evaluation of the short-range pairwise interactions in an N-Body simulation can be achieved using many different algorithms and parallelization techniques. Depending on the nature of the scenario, its current state, and the forces of interest, the optimal algorithm configuration can differ greatly. Choosing this optimum is a non-trivial task even for experts. Furthermore, this optimum can change over the course of a simulation. Typically, a particle simulation software only implements one algorithm for force computation and is thus specialized for a certain type of simulation. It is up to the user to choose the program suitable for his needs. Solution method: The AutoPas library implements a range of state of the art algorithms to find the relevant neighbors for the N-Body pairwise force calculation. It provides multiple shared-memory parallelization strategies using OpenMP and further algorithm optimization parameters that can all be set at run-time. A big burden for users persists in requiring the expert knowledge to pick the optimal solution procedure for a simulation. AutoPas removes this burden by tuning all aforementioned options automatically and dynamically. This way, simulation programs that make use of AutoPas give every domain scientist the possibility to make use of the most suitable algorithm configuration for arbitrary scenarios. [ABSTRACT FROM AUTHOR]