The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Ali Khan (University of North Texas), Sanjukta Bhowmick (University of North Texas), Michela Taufer (University of Tennessee, Knoxville)
Supervisor: Sanjukta Bhowmick (University of North Texas)
Abstract: Graph motifs—small subgraphs such as triangles and cliques—are key tools for comparing and aligning networks in domains ranging from biology to social sciences. While recent advances enable motif counting in billion-edge networks, existing methods focus mainly on global frequencies. Building on ParaDyMS, we introduce a method to compute local edge-level motif frequencies, capturing the motifs incident to each edge. Experiments on real-world networks show that our approach achieves competitive performance against state-of-the-art static algorithms and demonstrate its scalability on shared memory systems and GPUs.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF