Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Modellierung und Analyse komplexer Systeme

Aktuelles / News

Paper accepted at ECML PKDD '24

  • 17.07.24: Our paper Introducing Total Harmonic Resistance for Graph Robustness under Edge Deletions (authors: L. Berner, H. Meyerhenke) has been accepted at ECML PKDD 2024. The paper proposes a new graph robustness measure that can also handle disconnected graphs, a useful property for measuring how deleting edges changes the robustness of a graph.


Journal paper accepted by Information Sciences

  • 22.06.24: Our paper Generic Network Sparsification via Degree- and Subgraph-based Edge Sampling (authors: Z. Su, Y. Liu, J. Kurths, H. Meyerhenke) has been accepted by Information Sciences, Elsevier. The paper proposes new methods to sparsify a graph in a property-preserving manner for faster downstream analysis.


Paper accepted at ICPP'24

  • 10.06.24: Our paper Mapping Large Memory-constrained Workflows onto Heterogeneous Platforms (authors: S. Kulagina, H. Meyerhenke, A. Benoit) has been accepted at the ICPP'24. The paper presents an algorithm for scheduling workflows on a heterogeneous execution environment with constrained memory sizes.


Three interns support our team this summer

  • 01.06.24: We welcome three student interns, who work on projects of ours this summer: Isaline Plaid (ENS Lyon, France), Hazel Chen (DAAD scholarship), and Caolinn Hukill (DAAD scholarship). Welcome to the team!


Journal paper published in Social Network Analysis and Mining

  • 27.10.23: Our paper Greedy optimization of resistance-based graph robustness with global and local edge insertions. (M. Predari, L. Berner, R. Kooij, H. Meyerhenke) has been accepted for and published in Social Network Analysis and Mining 2023, Volume 13 (Springer Nature).


New team member: Ranran (Alice) Wang

  • 01.10.23: We welcome Ranran Wang as a new visiting PhD student. Her professional background includes information diffusion in networks. All the best for her studies!


Release 1.0 of simexpal - Simplifying Experimental Algorithmics

  • 27.09.23: We are happy to announce the release v1.0 of our software simexpal! The name stands for "Simplifying Experimental Algorithmics". It is a toolbox to manage, launch, monitor and evaluate your experiments on algorithms (e.g. benchmarking). The goal is to automate various repetitive tasks that occur whenever such experiments need to be executed.

    simexpal consists of both a command line (CLI) utility and a Python package. You can start using simexpal by installing it via pip or conda, e.g. "pip install simexpal" or "conda install simexpal". The documentation and examples for usage can be found on Read the Docs:

    The main page for development is on Github: Please feel encouraged to open Issues to provide feedback on documentation, or to report any bugs you encounter!


New team member: Msc. Florian Willich

  • 01.07.23: We welcome Florian Willich as a new PhD student! His professional background includes distributed graph datastructure. Check out the team website for more infos.


Paper accepted to Concurrency and Computation: Practice and Experience Journal

  • 07.06.23: Our paper Mapping Tree-shaped Workflows on Systems with Different Memory Sizes and Processor Speeds (authors: Kulagina, Meyerhenke, Benoit) has been accepted by the Wiley's Concurrency and Computation: Practice and Experience.


Paper published ACM Computing Surveys

  • 07.06.23: Our paperMore Recent Advances in (Hyper)Graph Partitioning by Ü. Çatalyürek, K. Devine, M. Fonseca Faraj, L. Gottesbüren, T. Heuer, H. Meyerhenke, P. Sanders, S. Schlag, C. Schulz, D. Seemaier and D. Wagner has been published in ACM Computing Surveys.


Three papers accepted (SBAC-PAD and ASONAM)

  • 11.09.22: This was a very successful weekend for the MACSy group with three papers being accepted at the conferences SBAC-PAD (parallel/distributed computing) and ASONAM (network science):
    • At SBAC-PAD: "An MPI-Parallel Algorithm for Static and Dynamic Top-k Harmonic Centrality" by van der Grinten, Custers (TU Delft), Le Thanh and Meyerhenke
    • At ASONAM: "Faster Greedy Optimization of Resistance-based Graph Robustness" by Predari, Kooij (TU Delft) and Meyerhenke
    • At ASONAM: "Network Sparsification via Degree- and Subgraph-based Edge Sampling" by Su, Kurths (PIK Potsdam) and Meyerhenke

The papers will soon be available on arXiv and (somewhat later) in the respective conference proceedings.


Paper accepted for EuroPar Workshop HeteroPar 2022

  • 01.07.22: Our paper Mapping Tree-shaped Workflows on Memory-heterogeneous Architectures (authors: Kulagina, Meyerhenke, Benoit) has been accepted by the HeteroPar workshop.


Journal papers accepted

  • 24.03.22: Our journal paper A Batch-Dynamic Suitor Algorithm for Approximating Maximum Weighted Matching (authors: Angriman, Boron, Meyerhenke) has been accepted by ACM J. on Experimental Algorithmics (JEA).
  • 15.03.22: Our journal paper The climatic interdependence of extreme-rainfall events around the globe, written as part of a joint PhD supervision with PIK Potsdam (authors: Su, Meyerhenke, Kurths), has been accepted by the journal Chaos.
  • 14.03.22: Our journal paper Scalable Katz Ranking Computation in Large Static and Dynamic Graphs, an extension of the corresponding ESA'18 paper written with US colleagues, has been accepted by ACM J. on Experimental Algorithmics (JEA). Congratulations to all co-authors (van der Grinten, Bergamini, Green, Bader, Meyerhenke)! The paper is also available as preliminary version via ACM.



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