187 citations · 581 across the 39 of their papers we have counts for
6 papers · 1 filter
Distributing Sparse Matrix/Graph Applications in Heterogeneous Clusters -- an Experimental Study
Charilaos Tzovas, Maria Predari, Henning Meyerhenke
Many problems in scientific and engineering applications contain sparse matrices or graphs as main input objects, e.g. numerical simulations on meshes. Large inputs are abundant th…
Group-Harmonic and Group-Closeness Maximization -- Approximation and Engineering
Eugenio Angriman, Ruben Becker, Gianlorenzo D'Angelo +3
Centrality measures characterize important nodes in networks. Efficiently computing such nodes has received a lot of attention. When considering the generalization of computing cen…
Systematic partitioning of proteins for quantum-chemical fragmentation methods using graph algorithms
Mario Wolter, Moritz von Looz, Henning Meyerhenke +1
Quantum-chemical fragmentation methods offer an efficient approach for the treatment of large proteins, in particular if local target quantities such as protein--ligand interaction…
Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis
Eugenio Angriman, Maria Predari, Alexander van der Grinten +1
The ubiquity of massive graph data sets in numerous applications requires fast algorithms for extracting knowledge from these data. We are motivated here by three electrical measur…
Combined Centrality Measures for an Improved Characterization of Influence Spread in Social Networks
Mehmet Simsek, Henning Meyerhenke
Influence Maximization (IM) aims at finding the most influential users in a social network, i. e., users who maximize the spread of an opinion within a certain propagation model. P…
High-Quality Hierarchical Process Mapping
Marcelo Fonseca Faraj, Alexander van der Grinten, Henning Meyerhenke +2
Partitioning graphs into blocks of roughly equal size such that few edges run between blocks is a frequently needed operation when processing graphs on a parallel computer. When a…