Deterministic Parallel Hypergraph Partitioning

Balanced hypergraph partitioning is a classical NP-hard optimization problem with applications in various domains such as VLSI design, simulating quantum circuits, optimizing data placement in distributed databases or minimizing communication volume in high performance computing. Engineering parallel partitioning heuristics is a topic of recent research, yet most of them are non-deterministic. In this work, we design and implement a highly scalable deterministic algorithm in the parallel partitioning framework Mt-KaHyPar. On our extensive set of benchmark instances, it achieves similar partition quality and performance as a comparable but non-deterministic configuration of Mt-KaHyPar and outperforms the only other parallel deterministic algorithm BiPart regarding partition quality, running time and speedups.