K-way Hypergraph Partitioning Research Articles

Net Clusting Based Low Complexity Coarsening Algorithm In k-way Hypergraph Partitioning

With the increasing scale of integrated circuits, hypergraph partitioning is usually applied to Very Large Scale Integration (VLSI) circuit layout and other applications to reduce the computational complexity. However, if without properly coarsening, the hypergraph partitioning problem will become intractable along with the increase of the number of vertices. In this paper, we propose a coarsening algorithm in k-way hypergraph partitioning based on net clustering, where net clustering is used to obtain the initial set of vertices with higher internal similarity. Due to the property of nets connecting through vertices, the proposal can cluster the net by local search and discard unimportant vertices from net clusters to achieve high-quality solutions. The experimental results show that our proposal achieves a high quality of coarsening with lower complexity. Even as the number of partitions rises, the computation time reduction will obviously increase. In the case of setting the number of partitions as 8, our algorithm can achieve almost the same partitioning quality as traditional hMetis, but with a time consumption reduction of 50%.

Multi-level direct K-way hypergraph partitioning with multiple constraints and fixed vertices

K -way hypergraph partitioning has an ever-growing use in parallelization of scientific computing applications. We claim that hypergraph partitioning with multiple constraints and fixed vertices should be implemented using direct K -way refinement, instead of the widely adopted recursive bisection paradigm. Our arguments are based on the fact that recursive-bisection-based partitioning algorithms perform considerably worse when used in the multiple constraint and fixed vertex formulations. We discuss possible reasons for this performance degradation. We describe a careful implementation of a multi-level direct K -way hypergraph partitioning algorithm, which performs better than a well-known recursive-bisection-based partitioning algorithm in hypergraph partitioning with multiple constraints and fixed vertices. We also experimentally show that the proposed algorithm is effective in standard hypergraph partitioning.