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
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.