6 Search Results for "Brandes, Ulrik"

Document
DOI: 10.4230/LIPIcs.SEA.2023.5
Engineering Shared-Memory Parallel Shuffling to Generate Random Permutations In-Place

Authors: Manuel Penschuck

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
Shuffling is the process of placing elements into a random order such that any permutation occurs with equal probability. It is an important building block in virtually all scientific areas. We engineer, - to the best of our knowledge - for the first time, a practically fast, parallel shuffling algorithm with O(√n log n) parallel depth that requires only poly-logarithmic auxiliary memory (with high probability). In an empirical evaluation, we compare our implementations with a number of existing solutions on various computer architectures. Our algorithms consistently achieve the highest through-put on all machines. Further, we demonstrate that the runtime of our parallel algorithm is comparable to the time that other algorithms may take to acquire the memory from the operating system to copy the input.
Cite as

Manuel Penschuck. Engineering Shared-Memory Parallel Shuffling to Generate Random Permutations In-Place. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 5:1-5:20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{penschuck:LIPIcs.SEA.2023.5,
  author =	{Penschuck, Manuel},
  title =	{{Engineering Shared-Memory Parallel Shuffling to Generate Random Permutations In-Place}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{5:1--5:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.5},
  URN =		{urn:nbn:de:0030-drops-183550},
  doi =		{10.4230/LIPIcs.SEA.2023.5},
  annote =	{Keywords: Shuffling, random permutation, parallelism, in-place, algorithm engineering, practical implementation}
}
Document
DOI: 10.4230/LIPIcs.SEA.2023.6
Proxying Betweenness Centrality Rankings in Temporal Networks

Authors: Ruben Becker, Pierluigi Crescenzi, Antonio Cruciani, and Bojana Kodric

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
Identifying influential nodes in a network is arguably one of the most important tasks in graph mining and network analysis. A large variety of centrality measures, all aiming at correctly quantifying a node’s importance in the network, have been formulated in the literature. One of the most cited ones is the betweenness centrality, formally introduced by Freeman (Sociometry, 1977). On the other hand, researchers have recently been very interested in capturing the dynamic nature of real-world networks by studying temporal graphs, rather than static ones. Clearly, centrality measures, including the betweenness centrality, have also been extended to temporal graphs. Buß et al. (KDD, 2020) gave algorithms to compute various notions of temporal betweenness centrality, including the perhaps most natural one - shortest temporal betweenness. Their algorithm computes centrality values of all nodes in time O(n³ T²), where n is the size of the network and T is the total number of time steps. For real-world networks, which easily contain tens of thousands of nodes, this complexity becomes prohibitive. Thus, it is reasonable to consider proxies for shortest temporal betweenness rankings that are more efficiently computed, and, therefore, allow for measuring the relative importance of nodes in very large temporal graphs. In this paper, we compare several such proxies on a diverse set of real-world networks. These proxies can be divided into global and local proxies. The considered global proxies include the exact algorithm for static betweenness (computed on the underlying graph), prefix foremost temporal betweenness of Buß et al., which is more efficiently computable than shortest temporal betweenness, and the recently introduced approximation approach of Santoro and Sarpe (WWW, 2022). As all of these global proxies are still expensive to compute on very large networks, we also turn to more efficiently computable local proxies. Here, we consider temporal versions of the ego-betweenness in the sense of Everett and Borgatti (Social Networks, 2005), standard degree notions, and a novel temporal degree notion termed the pass-through degree, that we introduce in this paper and which we consider to be one of our main contributions. We show that the pass-through degree, which measures the number of pairs of neighbors of a node that are temporally connected through it, can be computed in nearly linear time for all nodes in the network and we experimentally observe that it is surprisingly competitive as a proxy for shortest temporal betweenness.
Cite as

Ruben Becker, Pierluigi Crescenzi, Antonio Cruciani, and Bojana Kodric. Proxying Betweenness Centrality Rankings in Temporal Networks. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 6:1-6:22, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{becker_et_al:LIPIcs.SEA.2023.6,
  author =	{Becker, Ruben and Crescenzi, Pierluigi and Cruciani, Antonio and Kodric, Bojana},
  title =	{{Proxying Betweenness Centrality Rankings in Temporal Networks}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{6:1--6:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.6},
  URN =		{urn:nbn:de:0030-drops-183568},
  doi =		{10.4230/LIPIcs.SEA.2023.6},
  annote =	{Keywords: node centrality, betweenness, temporal graphs, graph mining}
}
Document
DOI: 10.4230/LIPIcs.SEA.2023.15
FREIGHT: Fast Streaming Hypergraph Partitioning

Authors: Kamal Eyubov, Marcelo Fonseca Faraj, and Christian Schulz

Published in: LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Abstract
Partitioning the vertices of a (hyper)graph into k roughly balanced blocks such that few (hyper)edges run between blocks is a key problem for large-scale distributed processing. A current trend for partitioning huge (hyper)graphs using low computational resources are streaming algorithms. In this work, we propose FREIGHT: a Fast stREamInG Hypergraph parTitioning algorithm which is an adaptation of the widely-known graph-based algorithm Fennel. By using an efficient data structure, we make the overall running of FREIGHT linearly dependent on the pin-count of the hypergraph and the memory consumption linearly dependent on the numbers of nets and blocks. The results of our extensive experimentation showcase the promising performance of FREIGHT as a highly efficient and effective solution for streaming hypergraph partitioning. Our algorithm demonstrates competitive running time with the Hashing algorithm, with a difference of a maximum factor of four observed on three fourths of the instances. Significantly, our findings highlight the superiority of FREIGHT over all existing (buffered) streaming algorithms and even the in-memory algorithm HYPE, with respect to both cut-net and connectivity measures. This indicates that our proposed algorithm is a promising hypergraph partitioning tool to tackle the challenge posed by large-scale and dynamic data processing.
Cite as

Kamal Eyubov, Marcelo Fonseca Faraj, and Christian Schulz. FREIGHT: Fast Streaming Hypergraph Partitioning. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 15:1-15:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{eyubov_et_al:LIPIcs.SEA.2023.15,
  author =	{Eyubov, Kamal and Fonseca Faraj, Marcelo and Schulz, Christian},
  title =	{{FREIGHT: Fast Streaming Hypergraph Partitioning}},
  booktitle =	{21st International Symposium on Experimental Algorithms (SEA 2023)},
  pages =	{15:1--15:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-279-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{265},
  editor =	{Georgiadis, Loukas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.15},
  URN =		{urn:nbn:de:0030-drops-183657},
  doi =		{10.4230/LIPIcs.SEA.2023.15},
  annote =	{Keywords: Hypergraph partitioning, graph partitioning, edge partitioning, streaming}
}
Document
DOI: 10.4230/DagRep.5.1.243
Empirical Evaluation for Graph Drawing (Dagstuhl Seminar 15052)

Authors: Ulrik Brandes, Irene Finocchi, Martin Nöllenburg, and Aaron Quigley

Published in: Dagstuhl Reports, Volume 5, Issue 1 (2015)

Abstract
This report documents the program and outcomes of Dagstuhl Seminar 15052 "Empirical Evaluation for Graph Drawing" which took place January 25-30, 2015. The goal of the seminar was to advance the state of the art in experimental evaluation within the wider field of graph drawing, both with respect to user studies and algorithmic experimentation.
Cite as

Ulrik Brandes, Irene Finocchi, Martin Nöllenburg, and Aaron Quigley. Empirical Evaluation for Graph Drawing (Dagstuhl Seminar 15052). In Dagstuhl Reports, Volume 5, Issue 1, pp. 243-258, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2015)

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@Article{brandes_et_al:DagRep.5.1.243,
  author =	{Brandes, Ulrik and Finocchi, Irene and N\"{o}llenburg, Martin and Quigley, Aaron},
  title =	{{Empirical Evaluation for Graph Drawing (Dagstuhl Seminar 15052)}},
  pages =	{243--258},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{5},
  number =	{1},
  editor =	{Brandes, Ulrik and Finocchi, Irene and N\"{o}llenburg, Martin and Quigley, Aaron},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.1.243},
  URN =		{urn:nbn:de:0030-drops-50414},
  doi =		{10.4230/DagRep.5.1.243},
  annote =	{Keywords: graph drawing, experimental design, algorithm engineering, user studies, empirical evaluation, information visualization}
}
Document
DOI: 10.4230/DagSemProc.08191.4
08191 Working Group Report – Visualization of Trajectories

Authors: Stephen Borgatti, Ulrik Brandes, Michael Kaufmann, Stephen Kobourov, Anna Lubiw, and Dorothea Wagner

Published in: Dagstuhl Seminar Proceedings, Volume 8191, Graph Drawing with Applications to Bioinformatics and Social Sciences (2008)

Abstract
We considered the following problem: Given a set of vertices V and a set of paths P, where each path is a sequence of vertices, represent these paths somehow. We explored representations in different dimensions and with different conditions on the paths.
Cite as

Stephen Borgatti, Ulrik Brandes, Michael Kaufmann, Stephen Kobourov, Anna Lubiw, and Dorothea Wagner. 08191 Working Group Report – Visualization of Trajectories. In Graph Drawing with Applications to Bioinformatics and Social Sciences. Dagstuhl Seminar Proceedings, Volume 8191, pp. 1-3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2008)

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@InProceedings{borgatti_et_al:DagSemProc.08191.4,
  author =	{Borgatti, Stephen and Brandes, Ulrik and Kaufmann, Michael and Kobourov, Stephen and Lubiw, Anna and Wagner, Dorothea},
  title =	{{08191 Working Group Report – Visualization of Trajectories}},
  booktitle =	{Graph Drawing with Applications to Bioinformatics and Social Sciences},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8191},
  editor =	{Stephen P. Borgatti and Stephen Kobourov and Oliver Kohlbacher and Petra Mutzel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08191.4},
  URN =		{urn:nbn:de:0030-drops-15558},
  doi =		{10.4230/DagSemProc.08191.4},
  annote =	{Keywords: Graph drawing, trajectories, paths}
}
Document
DOI: 10.4230/DagSemRep.314
Link Analysis and Visualization (Dagstuhl Seminar 01271)

Authors: Ulrik Brandes, David Krackhardt, Roberto Tamassia, and Dorothea Wagner

Published in: Dagstuhl Seminar Reports. Dagstuhl Seminar Reports, Volume 1 (2021)

Abstract
Cite as

Ulrik Brandes, David Krackhardt, Roberto Tamassia, and Dorothea Wagner. Link Analysis and Visualization (Dagstuhl Seminar 01271). Dagstuhl Seminar Report 314, pp. 1-16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2002)

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@TechReport{brandes_et_al:DagSemRep.314,
  author =	{Brandes, Ulrik and Krackhardt, David and Tamassia, Roberto and Wagner, Dorothea},
  title =	{{Link Analysis and Visualization (Dagstuhl Seminar 01271)}},
  pages =	{1--16},
  ISSN =	{1619-0203},
  year =	{2002},
  type = 	{Dagstuhl Seminar Report},
  number =	{314},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemRep.314},
  URN =		{urn:nbn:de:0030-drops-151988},
  doi =		{10.4230/DagSemRep.314},
}
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