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G-kway: Multilevel GPU-Accelerated k-way Graph Partitioner

Wan-Luan Lee, Dian-Lun Lin, Tsung-Wei Huang, Shui Jiang, Tsung-Yi Ho, Yibo Lin, Bei Yu

2024Year
24Citations

Abstract

Graph partitioning is important for the design of many CAD algorithms. However, as the graph size continues to grow, graph partitioning becomes increasingly time-consuming. To overcome these challenges, we propose G-kway, an efficient multilevel GPU-accelerated k-way graph partitioner. G-kway introduces an effective union find-based coarsening and a novel independent set-based refinement algorithm to significantly accelerate both the coarsening and uncoarsening stages. Experimental results have shown that G-kway outperforms both the state-of-the-art CPU-based and GPU-based parallel partitioners with an average speedup of 8.6× and 3.8×, respectively, while achieving comparable partitioning quality.

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