LEADER 05112nam 2200601 450 001 9910811759503321 005 20220901064853.0 010 $a0-8218-9869-8 035 $a(CKB)3360000000463963 035 $a(EBL)3113242 035 $a(SSID)ssj0001034522 035 $a(PQKBManifestationID)11572437 035 $a(PQKBTitleCode)TC0001034522 035 $a(PQKBWorkID)11015818 035 $a(PQKB)11381231 035 $a(MiAaPQ)EBC3113242 035 $a(RPAM)17649154 035 $a(PPN)19710231X 035 $a(EXLCZ)993360000000463963 100 $a20140613h20132013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aGraph partitioning and graph clustering $e10th DIMACS Implementation Challenge Workshop, February 13-14, 2012, Georgia Institute of Technology, Atlanta, GA /$fDavid A. Bader [and three others], editors 210 1$aProvidence, Rhode Island :$cAmerican Mathematical Society,$d2013. 210 4$dİ2013 215 $a1 online resource (258 p.) 225 1 $aContemporary mathematics,$x1098-3627 ;$v588$x0271-4132 300 $aDescription based upon print version of record. 311 $a0-8218-9038-7 320 $aIncludes bibliographical references. 327 $aPreface -- 1. Introducing the 10th Challenge " Graph Partitioning and Graph Clustering -- 2. Key Results -- 3. Challenge Description -- 4. Contributions to this Collection -- 5. Directions for Further Research -- High quality graph partitioning -- 1. Introduction -- 2. Preliminaries -- 3. Related Work -- 4. Karlsruhe Fast Flow Partitioner -- 5. KaFFPa Evolutionary -- 6. Experiments -- 7. Conclusion and Future Work -- References -- Abusing a hypergraph partitioner for unweighted graph partitioning -- 1. Introduction -- 2. Mondriaan -- 3. Results -- 4. Conclusion -- References -- Parallel partitioning with Zoltan: Is hypergraph partitioning worth it? -- 1. Introduction -- 2. Models and Metrics -- 3. Overview of the Zoltan Hypergraph Partitioner -- 4. Experiments -- 5. Conclusions -- Acknowledgements -- References -- UMPa: A multi-objective, multi-level partitioner for communication minimization -- 1. Introduction -- 2. Background -- 3. UMPa: A multi-objective partitioning tool for communication minimization -- 4. Experimental results -- 5. Conclusions and future work -- References -- Appendix A. DIMACS Challenge Results -- Shape optimizing load balancing for MPI-parallel adaptive numerical simulations -- 1. Introduction -- 2. Related Work -- 3. Diffusion-based Repartitioning with DibaP -- 4. PDibaP: Parallel DibaP for Repartitioning -- 5. Experiments -- 6. Conclusions -- References -- Graph partitioning for scalable distributed graph computations -- 1. Introduction -- 2. Parallel Breadth-first Search -- 3. Analysis of Communication Costs -- 4. Graph and Hypergraph Partitioning Metrics -- 5. Experimental Setup -- 6. Microbenchmarking Collectives Performance -- 7. Performance Analysis and Results -- 8. Conclusions and Future Work -- Acknowledgments -- References -- Appendix on edge count per processor -- Using graph partitioning for efficient network modularity optimization -- 1. Introduction -- 2. Reduction of modularity optimization to minimum weighted cut -- 3. Implementation of the modularity optimization algorithm based on the Metis package -- 4. Comparison on DIMACS testbed graphs -- 5. Conclusion -- References -- Modularity maximization in networks by variable neighborhood search -- 1. Introduction -- 2. Description of the heuristic -- 3. Description of the exact method -- 4. Experimental Results -- 5. Conclusion -- References -- Network clustering via clique relaxations: A community based approach -- 1. Introduction -- 2. Background -- 3. Clustering Algorithm -- 4. Computational Results -- 5. Conclusion -- Acknowledgements -- References -- Identifying base clusters and their application to maximizing modularity -- Complete hierarchical cut-clustering: A case study on expansion and modularity -- A partitioning-based divisive clustering technique for maximizing the modularity -- An ensemble learning strategy for graph clustering -- Parallel community detection for massive graphs -- Graph coarsening and clustering on the GPU. 410 0$aContemporary mathematics (American Mathematical Society).$v588$x0271-4132 606 $aGraph algorithms$vCongresses 606 $aGraph theory$vCongresses 615 0$aGraph algorithms 615 0$aGraph theory 676 $a511/.5 686 $a05C85$a68W05$a05C82$a68W10$a68R10$a05C50$a05C65$2msc 702 $aBader$b David A.$f1969- 712 02$aAmerican Mathematical Society, 712 02$aCenter for Discrete Mathematics, 712 02$aTheoretical Computer Science, 712 12$aDIMACS Implementation Challenge Workshop 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910811759503321 996 $aGraph partitioning and graph clustering$9833096 997 $aUNINA