Compact graph representations and parallel connectivity algorithms for massive dynamic network analysis

Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication traffic, and scientific computing can be intuitively modeled as graphs. We present the first study of novel highperformance combinatorial techniques for analyzing largescale information networks, encapsulating dynamic interaction data in the order of billions of entities. We present new data structures to represent dynamic interaction networks, and discuss algorithms for processing parallel insertions and deletions of edges in small-world networks. With these new approaches, we achieve an average performance rate of 25 million structural updates per second and a parallel speedup of nearly 28 on a 64-way Sun UltraSPARC T2 multicore processor, for insertions and deletions to a small-world network of 33.5 million vertices and 268 million edges. We also design parallel implementations of fundamental dynamic gra...

• Type: Conference
• Year: 2009
• Where: IPPS
• Authors: Kamesh Madduri, David A. Bader
• Keywords: Distributed And Parallel Computing, Dynamic Interaction, IPPS 2009, Small-world Network, Small-world Network Analysis