A multithreaded algorithm for network alignment via approximate matching

  • Authors:

  • Arif M. Khan;David F. Gleich;Alex Pothen;Mahantesh Halappanavar

  • Affiliations:

  • Purdue University, West Lafayette, Indiana;Purdue University, West Lafayette, Indiana;Purdue University, West Lafayette, Indiana;Pacific Northwest National Laboratory

  • Venue:
  • SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
  • Year:
  • 2012

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Abstract

Network alignment is an optimization problem to find the best one-to-one map between the vertices of a pair of graphs that overlaps as many edges as possible. It is a relaxation of the graph isomorphism problem and is closely related to the subgraph isomorphism problem. The best current approaches are entirely heuristic and iterative in nature. They generate real-valued heuristic weights that must be rounded to find integer solutions. This rounding requires solving a bipartite maximum weight matching problem at each iteration in order to avoid missing high quality solutions. We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. We demonstrate almost a 20-fold speedup using 40 threads on an 8 processor Intel Xeon E7-8870 system and now solve real-world problems in 36 seconds instead of 10 minutes.