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This randomized trial uncovers efficient k-clique counting methods on GPUs, suggesting a path for enhanced graph analysis.
Counting k-cliques in a graph is an important problem in graph analysis with many applications such as community detection and graph partitioning. Counting k-cliques is typically done by traversing search trees starting at each vertex in the graph. Parallelizing k-clique counting has been well-studied on CPUs and many solutions exist. However, there are no performant solutions for k-clique counting on GPUs.
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Almasri et al. (2022) studied this question.
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