Parallel Maximum Clique Algorithms with Applications to Network Analysis

  title={Parallel Maximum Clique Algorithms with Applications to Network Analysis},
  author={Ryan A. Rossi and David F. Gleich and Assefaw Hadish Gebremedhin},
  journal={SIAM J. Sci. Comput.},
We present a fast, parallel maximum clique algorithm for large sparse graphs that is designed to exploit characteristics of social and information networks. The method exhibits a roughly linear runtime scaling over real-world networks ranging from a thousand to a hundred million nodes. In a test on a social network with 1.8 billion edges, the algorithm finds the largest clique in about 20 minutes. At its heart the algorithm employs a branch-and-bound strategy with novel and aggressive pruning… 

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