Publikationen

Falls Sie an einer Publikation interessiert sind, die nicht online erhältlich ist, senden Sie mir einfach eine E-Mail-Anfrage an mein nachname at kit dot edu!

Editorial Work

  • U.C. Meyer, H. Meyerhenke, A. Pinar, I. Safro: High-performance Graph Algorithms and Applications in Computational Science (Dagstuhl Seminar 14461). Dagstuhl Reports 4(11):40-58, March 2015.
    [DOI: 10.4230/DagRep.4.11.40] [bibtex]

  • G.F. Italiano, H. Meyerhenke, G.E. Blelloch, P. Tsigas: Topic 12: Theory and Algorithms for Parallel Computation - (Introduction). Euro-Par 2013: pp. 645-646.
    [DOI: 10.1007/978-3-642-40047-6_64] [bibtex]

  • D.A. Bader, H. Meyerhenke, P. Sanders, D. Wagner (eds.): Graph Partitioning and Graph Clustering. Proc. of the 10th DIMACS Implementation Challenge Workshop. AMS Contemporary Mathematics, 2013.
    [Book website at AMS]

  • G. Pucci, C.D. Zaroliagis, K.T. Herley, H. Meyerhenke: Topic 12: Theory and Algorithms for Parallel Computation. Euro-Par 2012: pp. 674-675.
    [DOI: 10.1007/978-3-642-32820-6_66] [bibtex]

Journal Papers

  • E. Bergamini, M. Borassi, P. Crescenzi, A. Marino, H. Meyerhenke: Computing Top-k Closeness Centrality Faster in Unweighted Graphs. In revision. Extended version of ALENEX'16 paper.
    [arXiv preprint]

  • E. Bergamini, P. Crescenzi, G. D'Angelo, H. Meyerhenke, L. Severini, Y. Velaj: Improving the Betweenness Centrality of a Node by Adding Links. In revision.
    [arXiv preprint]

  • C.L. Staudt, M. Hamann, A. Gutfraind, I. Safro, H. Meyerhenke: Generating realistic scaled complex networks. Accepted by Applied Network Science, Springer-Verlag. Extended version of Complex Networks 2016 paper.
    [arXiv preprint]

  • M. von Looz, H. Meyerhenke: Updating Dynamic Random Hyperbolic Graphs in Sublinear Time. Accepted. Extended version of IWOCA'16 paper.

  • R. Glantz, H. Meyerhenke: On finding convex cuts in general, bipartite and plane graphs. In Theoretical Computer Science 695: 54-73, September 2017. Elsevier. Extended version of CIAC'13 paper.
    [preliminary version at arXiv] [DOI: 10.1016/j.tcs.2017.07.026]

  • H. Meyerhenke, M. Nöllenburg, C. Schulz: Drawing Large Graphs by Multilevel Maxent-Stress Optimization. Accepted by IEEE Transactions on Visualization and Computer Graphics (TVCG). Extended version of GD'15 paper.
    [DOI: 10.1109/TVCG.2017.2689016]

  • H. Meyerhenke, P. Sanders, C. Schulz: Parallel Graph Partitioning for Complex Networks. In IEEE Transactions on Parallel and Distributed Systems 28(9): 2625-2638, September 2017. Extended version of IPDPS'15 paper.
    [preliminary conference version at arXiv][DOI: 10.1109/TPDS.2017.2671868]

  • C.L. Staudt, A. Sazonovs, H. Meyerhenke: NetworKit: A Tool Suite for Large-scale Network Analysis. In Network Science 4(4), pp. 508–530, December 2016. Cambridge University Press.
    [preliminary version at arXiv] [DOI: 10.1017/nws.2016.20]

  • D. Hoske, D. Lukarski, H. Meyerhenke, M. Wegner: Engineering a Combinatorial Laplacian Solver: Lessons Learned. In Algorithms 9(4): 72, December 2016. MDPI. Extended version of SEA'15 paper.
    [preliminary version] [DOI: 10.3390/a9040072]

  • H. Meyerhenke, P. Sanders, C. Schulz: Partitioning (Hierarchically Clustered) Complex Networks via Size-constrained Graph Clustering. In J. of Heuristics, 22(5), 759-782, October 2016. Springer-Verlag. Extended version of SEA'14 paper.
    [DOI: 10.1007/s10732-016-9315-8]

  • J. Koch, C.L. Staudt, M. Vogel, H. Meyerhenke: An Empirical Comparison of Big Graph Frameworks in the Context of Network Analysis. Social Network Analysis and Mining (SNAM), 6(1): 84:1-84:20 (2016), Springer Vienna. Extended version of FAB'15 paper.
    [arXiv preprint]
    [journal version at SpringerLink, DOI: 10.1007/s13278-016-0394-1]

  • E. Bergamini, H. Meyerhenke: Approximating Betweenness Centrality in Fully-dynamic Networks. In Internet Mathematics 12(5): 281-314 (2016). Taylor and Francis Group.
    Combines, updates, and extends our ALENEX'15 and ESA'15 papers.
    [arXiv preprint] [DOI: 10.1080/15427951.2016.1177802]

  • M. Hamann, G. Lindner, H. Meyerhenke, C.L. Staudt, D. Wagner: Structure-Preserving Sparsification Methods for Social Networks. Social Network Analysis and Mining (SNAM) 6(1): 22:1-22:22, December 2016. Springer Vienna. Extended version of ASONAM'15 paper.
    [arXiv preprint]
    [journal version at SpringerLink, DOI: 10.1007/s13278-016-0332-2]

  • R. Glantz, H. Meyerhenke, C. Schulz: Tree-based Coarsening and Partitioning of Complex Networks. ACM J. of Experimental Algorithmics (JEA), vol. 21, no. 1, article 1.6. ACM, January 2016. Special issue on SEA 2014.
    [arXiv preprint] [DOI: 10.1145/2851496]

  • C.L. Staudt, H. Meyerhenke: Engineering Parallel Algorithms for Community Detection in Massive Networks. IEEE Transactions on Parallel and Distributed Systems vol. 27, no. 1, pp. 171-184, 2016.
    Extended and updated version of ICPP'13 paper.
    [arXiv preprint] [DOI: 10.1109/TPDS.2015.2390633] (c) 2015 IEEE

  • X. Liu, P. R. Pande, H. Meyerhenke, D.A. Bader: PASQUAL: Parallel Techniques for Next Generation Genome Sequence Assembly. IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 5, pp. 977-986, May 2013.
    [abstract] [bibtex] [preprint (pdf)] [supplementary material (pdf)]
    [DOI: 10.1109/TPDS.2012.190]

  • H. Meyerhenke, T. Sauerwald: Beyond Good Partition Shapes: An Analysis of Diffusive Graph Partitioning. Algorithmica 64(3):329-361, November 2012. Special issue on ISAAC'10.
    [abstract] [bibtex] [preprint (pdf)]
    [DOI:10.1007/s00453-012-9666-y]

  • H. Meyerhenke, B. Monien, S. Schamberger: Graph Partitioning and Disturbed Diffusion. Parallel Computing, 35(10-11):544-569, 2009.
    [abstract] [bibtex] [preprint (gzipped pdf)]
    [DOI:10.1016/j.parco.2009.09.006]

  • H. Meyerhenke, B. Monien, T. Sauerwald: A New Diffusion-based Multilevel Algorithm for Computing Graph Partitions. Journal of Parallel and Distributed Computing, 69(9):750-761, 2009. Best Paper Awards and Panel Summary: 22nd International Parallel and Distributed Processing Symposium (IPDPS 2008).
    [abstract] [bibtex] [preprint (pdf)]
    [DOI: 10.1016/j.jpdc.2009.04.005]

Book Chapters

  • A. Buluc, H. Meyerhenke, I. Safro, P. Sanders, C. Schulz: Recent Advances in Graph Partitioning. In Algorithm Engineering: Selected Results and Surveys. LNCS 9220, Springer-Verlag, 2016.
    [arXiv preprint]

  • D.A. Bader, A. Kappes, H. Meyerhenke, P. Sanders, C. Schulz, D. Wagner: Benchmarking for Graph Clustering and Partitioning. Encyclopedia of Social Network Analysis and Mining, pp. 73-82. Springer-Verlag, 2014.
    [DOI: 10.1007/978-1-4614-7163-9_23-1]

  • D. Ediger, J. Riedy, D.A. Bader, H. Meyerhenke: Computational Graph Analytics for Massive Streaming Data. In Large-Scale Network-Centric Computing Systems (eds. H. Sarbazi-Azad and A. Y. Zomaya), John Wiley & Sons, 2013.
    [pdf at Wiley]

  • D. Ajwani, H. Meyerhenke: Realistic Computer Models. In: Matthias Müller-Hannemann, Stefan Schirra (eds.): Algorithm Engineering. Bridging the Gap between Algorithm Theory and Practice. Lecture Notes in Computer Science 5971, pp. 194-236. Springer-Verlag, 2010.
    [bibtex] [preprint (pdf)]

Preprints

Conference Papers (and Workshop Papers with Refereed Proceedings)

  • P. Bisenius, E. Bergamini, E. Angriman, H. Meyerhenke: Computing Top-k Closeness Centrality in Fully-dynamic Graphs. Accepted by 20th SIAM Algorithm Engineering & Experiments (ALENEX 2018).
    [arXiv preprint]

  • E. Bergamini, T. Gonser, H. Meyerhenke: Scaling up Group Closeness Maximization. Accepted by 20th SIAM Algorithm Engineering & Experiments (ALENEX 2018).
    [arXiv preprint]

  • M. Wegner, O. Taubert, A. Schug, H. Meyerhenke: Maxent-stress Optimization of 3D Biomolecular Models. In Proc. 25th European Symposium on Algorithms (ESA 2017).
    [published version at LIPIcs] [arXiv preprint]

  • E. Bergamini, H. Meyerhenke, M. Ortmann, A. Slobbe: Faster Betweenness Centrality Updates in Evolving Networks. In Proc. 16th Intl. Symposium on Experimental Algorithms (SEA 2017), pp. 23:1--23:16.
    [arXiv preprint]

  • R. Kimmig, H. Meyerhenke, D. Strash: Shared Memory Parallel Subgraph Enumeration. In Proc. 7th IEEE Workshop Parallel / Distributed Computing and Optimization (PDCO 2017), in conjunction with 31st IEEE International Parallel & Distributed Processing Symposium (IPDPS 2017), pp. 519-529. IEEE Computer Society, 2017.
    [arXiv preprint]

  • C.L. Staudt, M. Hamann, I. Safro, A. Gutfraind, H. Meyerhenke: Generating Scaled Replicas of Real-World Complex Networks. In Proc. 5th International Workshop on Complex Networks and their Applications. Springer-Verlag, 2016.
    [published version at SpringerLink] [arXiv preprint]

  • E. Bergamini, M. Wegner, D. Lukarski, H. Meyerhenke: Estimating Current-Flow Closeness Centrality with a Multigrid Laplacian Solver. In Proc. 7th SIAM Workshop on Combinatorial Scientific Computing (CSC 2016). SIAM, 2016.
    [published version at SIAM epubs] [arXiv preprint]

  • M. von Looz, M.S. Özdayi, S. Laue, H. Meyerhenke: Generating massive complex networks with hyperbolic geometry faster in practice. In Proc. 20th IEEE High Performance Extreme Computing Conference (HPEC 2016).
    [published version at IEEE Xplore] [arXiv preprint]

  • J. Kepner, P. Aaltonen, D. Bader, A. Buluc, F. Franchetti, J. Gilbert, D. Hutchison, M. Kumar, A. Lumsdaine, H. Meyerhenke, S. McMillan, J. Moreira, J.D. Owens, C. Yang, M. Zalewski, T. Mattson: Mathematical Foundations of the GraphBLAS. In Proc. 20th IEEE High Performance Extreme Computing Conference (HPEC 2016).
    [published version at IEEE Xplore] [arXiv preprint]

  • M. von Looz, H. Meyerhenke: Querying Probabilistic Neighborhoods in Spatial Data Sets Efficiently. In Proc. 27th International Workshop on Combinatorial Algorithms (IWOCA 2016), pp. 449-460. LNCS 9843, Springer-Verlag, 2016.
    [arXiv preprint]

  • M. von Looz, M. Wolter, C. Jacob, H. Meyerhenke: Better partitions of protein graphs for subsystem density-functional theory. In Proc. 15th Intl. Symposium on Experimental Algorithms (SEA 2016), pp. 1-16. LNCS 9685, Springer-Verlag, 2016.
    [arXiv preprint]

  • E. Bergamini, M. Borassi, P. Crescenzi, A. Marino, H. Meyerhenke: Computing Top-k Closeness Centrality Faster in Unweighted Graphs. In Proc. 18th SIAM Algorithm Engineering & Experiments (ALENEX 2016).
    [published version in SIAM epubs] [preprint]

  • S. Schlag, V. Henne, T. Heuer, H. Meyerhenke, P. Sanders, C. Schulz: k-way Hypergraph Partitioning via n-Level Recursive Bisection. In Proc. 18th SIAM Algorithm Engineering & Experiments (ALENEX 2016).
    [arXiv preprint]

  • M. von Looz, H. Meyerhenke, R. Prutkin: Generating Random Hyperbolic Graphs in Subquadratic Time. In Proc. 26th International Symposium on Algorithms and Computation (ISAAC 2015).
    [preliminary version at arXiv]

  • H. Meyerhenke, M. Nöllenburg, C. Schulz: Drawing Large Graphs by Multilevel Maxent-Stress Optimization. In Proc. 23rd International Symposium on Graph Drawing & Network Visualization (GD 2015).
    [arXiv preprint]

  • E. Bergamini, H. Meyerhenke: Fully-dynamic Approximation of Betweenness Centrality. In Proc. 23rd European Symposium on Algorithms (ESA 2015), pp. 155-166. LNCS 9294, Springer-Verlag, 2015.
    [published version at SpringerLink, DOI: 10.1007/978-3-662-48350-3_14]
    [arXiv preprint]

  • G. Lindner, C.L. Staudt, M. Hamann, H. Meyerhenke, D. Wagner: Structure-Preserving Sparsification of Social Networks. In Proc. IEEE/ACM Intl. Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015). Invited to Springer's Social Network Analysis and Mining (SNAM).
    [arXiv preprint]

  • J. Koch, C.L. Staudt, M. Vogel, H. Meyerhenke: Complex Network Analysis on Distributed Systems - An Empirical Comparison. In Proc. Intl. Symposium on Foundations and Applications of Big Data Analytics (FAB 2015). Recipient of the Best Paper Award. Invited to Springer's Social Network Analysis and Mining (SNAM).

  • D. Hoske, D. Lukarski, H. Meyerhenke, M. Wegner: Is Nearly-linear the same in Theory and Practice? A Case Study with a Combinatorial Laplacian Solver. In Proc. 14th Intl. Symp. on Experimental Algorithms (SEA 2015), pp. 205-218. LNCS 9125, Springer-Verlag, 2015.
    [arXiv preprint]

  • H. Meyerhenke, P. Sanders, C. Schulz: Parallel Graph Partitioning for Complex Networks. In Proc. 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2015), pp. 1055-1064. IEEE, Computer Society, 2015.
    [published version at IEEE Xplore, DOI: 10.1109/IPDPS.2015.18] (c) IEEE
    [arXiv preprint]

  • R. Glantz, H. Meyerhenke, A. Noe: Algorithms for Mapping Parallel Processes onto Grid and Torus Architectures. In Proc. 23rd Euromicro Intl. Conference on Parallel, Distributed and Network-based Processing (PDP 2015), pp. 236-243.
    [updated version at arXiv]

  • E. Bergamini, H. Meyerhenke, C.L. Staudt: Approximating Betweenness Centrality in Large Evolving Networks. In Proc. 17th SIAM Algorithm Engineering & Experiments (ALENEX 2015).
    [DOI: 10.1137/1.9781611973754.12] [arXiv preprint]

  • C.L. Staudt, Y. Marrakchi, H. Meyerhenke: Detecting Communities Around Seed Nodes in Complex Networks. In Proc. First International Workshop on High Performance Big Graph Data Management, Analysis, and Mining, co-located with the IEEE BigData 2014 conference.
    [published version at IEEE Xplore], (c) IEEE
    [preprint]

  • H. Meyerhenke, P. Sanders, C. Schulz: Partitioning Complex Networks via Size-constrained Clustering. In Proc. 13th Intl. Symp. on Experimental Algorithms (SEA 2014).
    [DOI: 10.1007/978-3-319-07959-2_30] [arXiv preprint]

  • R. Glantz, H. Meyerhenke, C. Schulz: Tree-based Coarsening and Partitioning of Complex Networks. In Proc. 13th Intl. Symp. on Experimental Algorithms (SEA 2014). Invited to special issue of ACM Journal of Experimental Algorithms (JEA).
    [DOI: 10.1007/978-3-319-07959-2_31] [arXiv preprint]

  • C.L. Staudt, H. Meyerhenke: Engineering High-Performance Community Detection Heuristics for Massive Graphs. In Proc. 42nd International Conference on Parallel Processing (ICPP 2013).
    [arXiv preprint]

  • R. Glantz, H. Meyerhenke: Finding all Convex Cuts of a Plane Graph. In Proc. 8th International Conference on Algorithms and Complexity (CIAC'13), LNCS 7878, pp. 246-263. Springer, 2013.
    [abstract] [bibtex] [arXiv preprint]

  • H. Meyerhenke: Shape Optimizing Load Balancing for MPI-Parallel Adaptive Numerical Simulations. In Graph Partitioning and Graph Clustering. Proc. 10th DIMACS Implementation Challenge. Contemporary Mathematics 588. AMS and DIMACS, 2013.
    [abstract] [pdf (preprint)]

  • E.J. Riedy, H. Meyerhenke. D. Ediger, D.A. Bader: Parallel Community Detection for Massive Graphs. In Graph Partitioning and Graph Clustering. Proc. 10th DIMACS Implementation Challenge. Contemporary Mathematics 588. AMS and DIMACS, 2013.
    [abstract] [pdf (preprint)]

  • C. Staudt, A. Schumm, H. Meyerhenke, R. Görke, D. Wagner: Static and Dynamic Aspects of Scientific Collaboration Networks. In Proc. 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'12), pp. 522-526. IEEE Computer Society, 2012.
    [abstract] [bibtex] [preprint]
    [DOI: http://doi.ieeecomputersociety.org/10.1109/ASONAM.2012.90]

  • J. Riedy, D.A. Bader, H. Meyerhenke: Scalable Multi-threaded Community Detection in Social Networks. In Proc. Workshop on Multi-Threaded Architectures and Applications (MTAAP'12), in conjunction with 26th IEEE Internatl. Parallel and Distributed Processing Symposium (IPDPS'12), IEEE, 2012.
    [abstract] [bibtex] [preprint (pdf)]

  • J. Riedy, H. Meyerhenke, D.A. Bader, D. Ediger, T. Mattson: Analysis of Streaming Social Networks on Multicore Architectures. In Proc. 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP'12).
    [abstract] [bibtex] [preprint (pdf)]

  • E.J. Riedy, H. Meyerhenke, D. Ediger, D.A. Bader: Parallel Community Detection for Massive Graphs. In Proc. 9th Intl. Conf. on Parallel Processing and Applied Mathematics (PPAM'11). LNCS 7203, pp. 286-296, Springer-Verlag, 2012.
    [abstract] [bibtex] [preprint (pdf)]
    [DOI: 10.1007/978-3-642-31464-3_29]

  • D. Ediger, J. Riedy, D.A. Bader, H. Meyerhenke: Tracking Structure of Streaming Social Networks. In Proc. Workshop on Multi-Threaded Architectures and Applications (MTAAP'11), in conjunction with 25th IEEE Internatl. Parallel and Distributed Processing Symposium (IPDPS'11), IEEE, 2011.
    [abstract] [bibtex] [preprint (pdf)]

  • H. Meyerhenke: Beyond Good Shapes: Diffusion-based Graph Partitioning is Relaxed Cut Optimization. In Proc. 21st International Symposium on Algorithms and Computation (ISAAC'10), Part II, LNCS 6507, pp. 387-398. Springer-Verlag 2010. Invited to special issue of Algorithmica.
    [abstract] [bibtex] [preprint (pdf)]

  • J. Gehweiler, H. Meyerhenke: A Distributed Diffusive Heuristic for Clustering a Virtual P2P Supercomputer. In Proc. 7th High-Performance Grid Computing Workshop (HPGC'10), in conjunction with 24th IEEE Internatl. Parallel and Distributed Processing Symposium (IPDPS'10), IEEE, 2010.
    [abstract] [bibtex] [preprint (pdf)]

  • H. Meyerhenke: Dynamic Load Balancing for Parallel Numerical Simulations based on Repartitioning with Disturbed Diffusion. In Proc. 15th Internatl. Conference on Parallel and Distributed Systems (ICPADS'09). IEEE, 2009.
    [abstract] [bibtex] [preprint (pdf)]

  • H. Meyerhenke, B. Monien, T. Sauerwald: A New Diffusion-based Multilevel Algorithm for Computing Graph Partitions of Very High Quality. In Proc. 22nd IEEE Internatl. Parallel and Distributed Processing Symposium (IPDPS'08). Recipient of the Best Algorithms Paper Award.
    [abstract] [bibtex] [preprint (pdf)] or [pdf at IEEE Xplore, © IEEE Computer Society 2008]

  • H. Meyerhenke, T. Sauerwald: Analyzing Disturbed Diffusion on Networks. In Proc. 17th International Symposium on Algorithms and Computation (ISAAC'06), LNCS 4288, pp. 429-438. Springer-Verlag, 2006.
    [abstract] [bibtex] [pdf, © Springer-Verlag, Berlin Heidelberg 2006]
    [DOI: 10.1007/11940128_44]

  • H. Meyerhenke, S. Schamberger: A Parallel Shape Optimizing Load Balancer. In Proc. 12th Int. Euro-Par Conf. 2006, LNCS 4128, pp. 232-242. Springer-Verlag, 2006.
    [abstract] [bibtex] [pdf, © Springer-Verlag, Berlin Heidelberg 2006]

  • H. Meyerhenke, B. Monien, S. Schamberger: Accelerating Shape Optimizing Load Balancing for Parallel FEM Simulations by Algebraic Multigrid. In Proc. 20th IEEE Internatl. Parallel and Distributed Processing Symposium (IPDPS'06), p. 57 (CD), IEEE Computer Society, 2006.
    [abstract] [bibtex] [preprint (pdf)] [pdf at IEEE Xplore, © IEEE Computer Society 2006]

  • H. Meyerhenke, S. Schamberger: Balancing Parallel Adaptive FEM Computations by Solving Systems of Linear Equations. In Proc. 11th Int. Euro-Par Conf. 2005, LNCS 3648, pp. 209-219. Springer-Verlag, 2005.
    [abstract] [bibtex] [pdf, © Springer-Verlag, Berlin Heidelberg 2005]

Selected Workshop Presentations (without Refereed Proceedings)

  • J. Kepner, D. Bader, A. Buluc, J. Gilbert, T. Mattson, H. Meyerhenke: Graphs, Matrices, and the GraphBLAS: Seven Good Reasons. Procedia Computer Science, Volume 51, 2015, pp. 2453-2462, ISSN 1877-0509. Special issue on International Conference On Computational Science (ICCS 2015).
    [bibtex] [arXiv preprint] [DOI: 10.1016/j.procs.2015.05.353]

  • H. Meyerhenke: Engineering Parallel Algorithms for Partitioning Problems in Graphs. Invited talk at Final Meeting of Priority Programme Algorithm Engineering, September 2014.

  • H. Meyerhenke, D. Wagner: Algorithmic Methods for Network Analysis. Invited tutorial at Summer School on Algorithm Engineering, Bad Herrenalb, September 2014.

  • C.L. Staudt, H. Meyerhenke: Engineering High-Performance Community Detection Heuristics for Massive Graphs. In Algorithm Engineering, 22.09. - 27.09.2013. Dagstuhl Seminar Proceedings 13391, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2013. Based on ICPP 2013 paper.

  • C.L. Staudt and H. Meyerhenke: Parallel Dynamic and Selective Community Detection in Massive Streaming Graphs. Presented at European Conference on Data Analysis (ECDA 2013), Luxembourg.

  • H. Meyerhenke, E.J. Riedy, D.A. Bader: Recent Trends in Graph Clustering. In Invited Session Graph Partitioning and Clustering of 21st International Symposium on Mathematical Programming (ISMP 2012). Berlin, Germany, August 19-24, 2012.

  • H. Meyerhenke, E.J. Riedy, D.A. Bader: Parallel Community Detection in Streaming Graphs. In Minisymposium on Parallel Analysis of Massive Social Networks, 15th SIAM Conference on Parallel Processing for Scientific Computing (PP12), Savannah, GA, February 15-17, 2012.

  • D. Ediger, E.J. Riedy, H. Meyerhenke, D.A. Bader: Analyzing Massive Networks with GraphCT. Poster Session, 15th SIAM Conference on Parallel Processing for Scientific Computing (PP12), Savannah, GA, February 15-17, 2012.

  • E.J. Riedy, D. Ediger, H. Meyerhenke, D.A. Bader: STING: Software for Analysis of Spatio-Temporal Interaction Networks and Graphs. Poster Session, 15th SIAM Conference on Parallel Processing for Scientific Computing (PP12), Savannah, GA, February 15-17, 2012.

  • B. Monien, H. Meyerhenke: Recent Trends in Graph Partitioning for Scientific Computing. Invited talk presented by Burkhard Monien at SIAM Workshop on Combinatorial Scientific Computing (CSC'11).
    [ppsx, 14MB]

  • H. Meyerhenke, B. Monien: On Multilevel Diffusion-based Load Balancing for Parallel Adaptive Numerical Simulations. Presented at SIAM Conference on Computational Science and Engineering (CSE'11), Reno, (Nevada, USA), February/March 2011.

  • H. Meyerhenke, J. Gehweiler: On Dynamic Graph Partitioning and Graph Clustering using Diffusion. In: Algorithm Engineering, 27.06. - 02.07.2010. Dagstuhl Seminar Proceedings 10261, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2010.
    [pdf]

  • H. Meyerhenke, B. Monien, S. Schamberger, T. Sauerwald: Graph Clustering based on Disturbed Diffusion. In Proc. Oberwolfach Workshop Algorithm Engineering, Math. Forschungsinstitut Oberwolfach Report No. 25/2007, pp. 1430-1431.
    [pdf at MFO]

  • H. Meyerhenke, B. Monien, T. Sauerwald: Parallel Graph Clustering Based on Disturbed Diffusion. In: Web Information Retrieval and Linear Algebra Algorithms, 11.02. - 16.02.2007. Dagstuhl Seminar Abstracts Collection 07071, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2007.
    [pdf at Dagstuhl]

  • B. Monien, S. Schamberger, U.-P. Schroeder, H. Meyerhenke: On Balancing of Dynamic Networks. In New Trends in Parallel & Distributed Computing, 6th Heinz Nixdorf Symposium (2006), HNI-Verlagsschriftenreihe, vol. 181, pp. 171-181.
    [preprint (pdf)]

  • H. Meyerhenke: Constructing Higher Order Voronoi Diagrams in Parallel. In European Workshop on Computational Geometry 2005, pp. 123-126.
    [pdf]

  • H. Meyerhenke: PFDC: A Parallel Algorithm for Fast Density-based Clustering in Large Spatial Databases. In Informatiktage 2002, Konradin Verlagsgruppe 2003, pp. 48 - 52.
    [pdf]

Reports

  • C. Staudt, A. Schumm, H. Meyerhenke, R. Görke, D. Wagner: Static and Dynamic Aspects of Scientific Collaboration Networks. Karlsruhe Reports in Informatics; 2012,11; ISSN: 2190-4782. June 2012.
    [html] [pdf]

  • H. Meyerhenke, B. Monien, T. Sauerwald. Parallel Graph Clustering based on Disturbed Diffusion. Technical Report tr-ri-07-280, Universität Paderborn, Jan. 2007.

  • H. Meyerhenke, H.-D. Hecker: Parallele Algorithmische Geometrie anhand von Delaunay-Triangulationen. Jenaer Schriften zur Mathematik und Informatik, Math/Inf/04/05. Friedrich-Schiller-Universität Jena, Mai 2005.
    [abstract]

  • H. Meyerhenke, H.-D. Hecker: Delaunay-Triangulation und Tiefensortierung auf grobkörnigen Parallelrechnern. Jenaer Schriften zur Mathematik und Informatik, Math/Inf/10/04. Friedrich-Schiller-Universität Jena, August 2004.
    [abstract]

  • H. Meyerhenke, H.-D. Hecker: Parallelverarbeitung von Delaunay-Triangulationen und Voronoi-Diagrammen höherer Ordnung. Jenaer Schriften zur Mathematik und Informatik, Math/Inf/09/04. Friedrich-Schiller-Universität Jena, August 2004.
    [abstract]

  • H. Meyerhenke: Fast Density-based Clustering in Parallel with Different Parallel K-d Tree Schemes. Jenaer Schriften zur Mathematik und Informatik, Math/Inf/17/02. Friedrich-Schiller-Universität Jena, November 2002.
    (ask me via e-mail for [pdf])

Theses

  • H. Meyerhenke: Disturbed Diffusive Schemes for Solving Partitioning Problems on Graphs. Dissertation, University of Paderborn, April 2008.
    [abstract (en)] [abstract (de)] [bibtex] [pdf]

  • H. Meyerhenke: Parallelverarbeitung spezieller Triangulationen. Diplomarbeit, Friedrich-Schiller-Universität Jena, August 2004.
    [pdf]