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Documents authored by Hübschle-Schneider, Lorenz

Document
DOI: 10.4230/LIPIcs.SEA.2022.4
Fast Succinct Retrieval and Approximate Membership Using Ribbon

Authors: Peter C. Dillinger, Lorenz Hübschle-Schneider, Peter Sanders, and Stefan Walzer

Published in: LIPIcs, Volume 233, 20th International Symposium on Experimental Algorithms (SEA 2022)

Abstract
A retrieval data structure for a static function f: S → {0,1}^r supports queries that return f(x) for any x ∈ S. Retrieval data structures can be used to implement a static approximate membership query data structure (AMQ), i.e., a Bloom filter alternative, with false positive rate 2^{-r}. The information-theoretic lower bound for both tasks is r|S| bits. While succinct theoretical constructions using (1+o(1))r|S| bits were known, these could not achieve very small overheads in practice because they have an unfavorable space-time tradeoff hidden in the asymptotic costs or because small overheads would only be reached for physically impossible input sizes. With bumped ribbon retrieval (BuRR), we present the first practical succinct retrieval data structure. In an extensive experimental evaluation BuRR achieves space overheads well below 1% while being faster than most previously used retrieval data structures (typically with space overheads at least an order of magnitude larger) and faster than classical Bloom filters (with space overhead ≥ 44%). This efficiency, including favorable constants, stems from a combination of simplicity, word parallelism, and high locality. We additionally describe homogeneous ribbon filter AMQs, which are even simpler and faster at the price of slightly larger space overhead.
Cite as

Peter C. Dillinger, Lorenz Hübschle-Schneider, Peter Sanders, and Stefan Walzer. Fast Succinct Retrieval and Approximate Membership Using Ribbon. In 20th International Symposium on Experimental Algorithms (SEA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 233, pp. 4:1-4:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{dillinger_et_al:LIPIcs.SEA.2022.4,
  author =	{Dillinger, Peter C. and H\"{u}bschle-Schneider, Lorenz and Sanders, Peter and Walzer, Stefan},
  title =	{{Fast Succinct Retrieval and Approximate Membership Using Ribbon}},
  booktitle =	{20th International Symposium on Experimental Algorithms (SEA 2022)},
  pages =	{4:1--4:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-251-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{233},
  editor =	{Schulz, Christian and U\c{c}ar, Bora},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2022.4},
  URN =		{urn:nbn:de:0030-drops-165385},
  doi =		{10.4230/LIPIcs.SEA.2022.4},
  annote =	{Keywords: AMQ, Bloom filter, dictionary, linear algebra, randomized algorithm, retrieval data structure, static function data structure, succinct data structure, perfect hashing}
}
Document
DOI: 10.4230/LIPIcs.ESA.2019.59
Parallel Weighted Random Sampling

Authors: Lorenz Hübschle-Schneider and Peter Sanders

Published in: LIPIcs, Volume 144, 27th Annual European Symposium on Algorithms (ESA 2019)

Abstract
Data structures for efficient sampling from a set of weighted items are an important building block of many applications. However, few parallel solutions are known. We close many of these gaps both for shared-memory and distributed-memory machines. We give efficient, fast, and practicable algorithms for sampling single items, k items with/without replacement, permutations, subsets, and reservoirs. We also give improved sequential algorithms for alias table construction and for sampling with replacement. Experiments on shared-memory parallel machines with up to 158 threads show near linear speedups both for construction and queries.
Cite as

Lorenz Hübschle-Schneider and Peter Sanders. Parallel Weighted Random Sampling. In 27th Annual European Symposium on Algorithms (ESA 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 144, pp. 59:1-59:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{hubschleschneider_et_al:LIPIcs.ESA.2019.59,
  author =	{H\"{u}bschle-Schneider, Lorenz and Sanders, Peter},
  title =	{{Parallel Weighted Random Sampling}},
  booktitle =	{27th Annual European Symposium on Algorithms (ESA 2019)},
  pages =	{59:1--59:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-124-5},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{144},
  editor =	{Bender, Michael A. and Svensson, Ola and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2019.59},
  URN =		{urn:nbn:de:0030-drops-111800},
  doi =		{10.4230/LIPIcs.ESA.2019.59},
  annote =	{Keywords: categorical distribution, multinoulli distribution, parallel algorithm, alias method, PRAM, communication efficient algorithm, subset sampling, reservoir sampling}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2014.138
Speed-Consumption Tradeoff for Electric Vehicle Route Planning

Authors: Moritz Baum, Julian Dibbelt, Lorenz Hübschle-Schneider, Thomas Pajor, and Dorothea Wagner

Published in: OASIcs, Volume 42, 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2014)

Abstract
We study the problem of computing routes for electric vehicles (EVs) in road networks. Since their battery capacity is limited, and consumed energy per distance increases with velocity, driving the fastest route is often not desirable and may even be infeasible. On the other hand, the energy-optimal route may be too conservative in that it contains unnecessary detours or simply takes too long. In this work, we propose to use multicriteria optimization to obtain Pareto sets of routes that trade energy consumption for speed. In particular, we exploit the fact that the same road segment can be driven at different speeds within reasonable intervals. As a result, we are able to provide routes with low energy consumption that still follow major roads, such as freeways. Unfortunately, the size of the resulting Pareto sets can be too large to be practical. We therefore also propose several nontrivial techniques that can be applied on-line at query time in order to speed up computation and filter insignificant solutions from the Pareto sets. Our extensive experimental study, which uses a real-world energy consumption model, reveals that we are able to compute diverse sets of alternative routes on continental networks that closely resemble the exact Pareto set in just under a second---several orders of magnitude faster than the exhaustive algorithm.
Cite as

Moritz Baum, Julian Dibbelt, Lorenz Hübschle-Schneider, Thomas Pajor, and Dorothea Wagner. Speed-Consumption Tradeoff for Electric Vehicle Route Planning. In 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 42, pp. 138-151, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{baum_et_al:OASIcs.ATMOS.2014.138,
  author =	{Baum, Moritz and Dibbelt, Julian and H\"{u}bschle-Schneider, Lorenz and Pajor, Thomas and Wagner, Dorothea},
  title =	{{Speed-Consumption Tradeoff for Electric Vehicle Route Planning}},
  booktitle =	{14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{138--151},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-75-0},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{42},
  editor =	{Funke, Stefan and Mihal\'{a}k, Mat\'{u}s},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2014.138},
  URN =		{urn:nbn:de:0030-drops-47583},
  doi =		{10.4230/OASIcs.ATMOS.2014.138},
  annote =	{Keywords: electric vehicles, shortest paths, route planning, bicriteria optimization, algorithm engineering}
}
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