The content discusses the importance of triangle counting algorithms and introduces a novel method using cover-edge sets to improve efficiency. It presents sequential and parallel algorithms, along with experimental results on real and synthetic graphs.
Listing and counting triangles in graphs is crucial for network analyses, including community detection, clustering coefficients, k-trusses, and triangle centrality. The proposed cover-edge set concept aims to find triangles more efficiently by skipping unnecessary edge checks. Novel sequential and parallel triangle counting algorithms are introduced based on cover-edge sets. The sequential algorithm competes well with previous approaches on real and synthetic graphs from benchmarks like Graph500. A distributed parallel algorithm is developed to reduce communication on massive graphs significantly. Experiments conducted on Intel Xeon processors shed light on the impact of graph attributes on algorithm performance.
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by David A. Bad... at arxiv.org 03-06-2024
https://arxiv.org/pdf/2403.02997.pdfDeeper Inquiries