Graph partitioning and graph clustering : 10th DIMACS Implementation Challenge Workshop, February 13-14, 2012, Georgia Institute of Technology, Atlanta, GA

Table of Contents Preface - by David A. Bader, Henning Meyerhenke, Peter Sanders, and Dorothea Wagner High quality graph partitioning - by P. Sanders and C. Schulz Abusing a Hypergraph Partitioner for Unweighted Graph Partitioning - by B. O. Fagginger Auer and R. H. Bisseling Parallel partitioning with Zoltan: Is hypergraph partitioning worth it? - by S. Rajamanickam and E. G. Boman UMPa: A multi-objective, multi-level partitioner for communication minimization - by U. V. Catalyurek, M. Deveci, K. Kaya, and K. Ucar Shape optimizing load balancing for MPI-parallel adaptive numerical simulations - by H. Meyerhenke Graph partitioning for scalable distributed graph computations - by A. Buluc and K. Madduri Using graph partitioning for efficient network modularity optimization - by H. Djidjev and M. Onus Modularity maximization in networks by variable neighborhood search - by D. Aloise, G. Caporossi, P. Hansen, L. Liberti, S. Perron, and M. Ruiz Network clustering via clique relaxations: A community based approach - by A. Verma and S. Butenko Identifying base clusters and their application to maximizing modularity - by S. Srinivasan, T. Chakraborty, and S. Bhowmick Complete hierarchical cut-clustering: A case study on expansion and modularity - by M. Hamann, T. Hartmann, and D. Wagner A partitioning-based divisive clustering technique for maximizing the modularity - by U. V. Catalyurek, K. Kaya, J. Langguth, and B. Ucar An ensemble learning strategy for graph clustering - by M. Ovelgonne and A. Geyer-Schulz Parallel community detection for massive graphs - by E. J. Riedy, H. Meyerhenke, D. Ediger, and D. A. Bader Graph coarsening and clustering on the GPU - by B. O. Fagginger Auer and R. H. Bisseling