7 Search Results for "Johnson, David S."


Document
Rethinking Experimental Methods in Computing (Dagstuhl Seminar 16111)

Authors: Daniel Delling, Camil Demetrescu, David S. Johnson, and Jan Vitek

Published in: Dagstuhl Reports, Volume 6, Issue 3 (2016)


Abstract
This report documents the talks and discussions at the Dagstuhl seminar 16111 "Rethinking Experimental Methods in Computing". The seminar brought together researchers from several computer science communities, including algorithm engineering, programming languages, information retrieval, high-performance computing, operations research, performance analysis, embedded systems, distributed systems, and software engineering. The main goals of the seminar were building a network of experimentalists and fostering a culture of sound quantitative experiments in computing. During the seminar, groups of participants have worked on distilling useful resources based on the collective experience gained in different communities and on planning actions to promote sound experimental methods and reproducibility efforts.

Cite as

Daniel Delling, Camil Demetrescu, David S. Johnson, and Jan Vitek. Rethinking Experimental Methods in Computing (Dagstuhl Seminar 16111). In Dagstuhl Reports, Volume 6, Issue 3, pp. 24-43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@Article{delling_et_al:DagRep.6.3.24,
  author =	{Delling, Daniel and Demetrescu, Camil and Johnson, David S. and Vitek, Jan},
  title =	{{Rethinking Experimental Methods in Computing (Dagstuhl Seminar 16111)}},
  pages =	{24--43},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{3},
  editor =	{Delling, Daniel and Demetrescu, Camil and Johnson, David S. and Vitek, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.3.24},
  URN =		{urn:nbn:de:0030-drops-61463},
  doi =		{10.4230/DagRep.6.3.24},
  annote =	{Keywords: Algorithms, Benchmarks, Data sets, Experiments, Repeatability, Reproducibility, Software Artifacts, Statistics}
}
Document
Algorithm Engineering (Dagstuhl Seminar 13391)

Authors: Andrew V. Goldberg, Giuseppe F. Italiano, David S. Johnson, and Dorothea Wagner

Published in: Dagstuhl Reports, Volume 3, Issue 9 (2014)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 13391 "Algorithm Engineering". The algorithm engineering approach consists of a cycle of algorithm design, analysis, implementation, and experimental evaluation, with the aim of bridging the gap between theory and practice in the area of algorithms. This cycle of phases is driven by falsifiable hypotheses validated by experiments. Moreover, real-world instances often have direct impact on this cycle since they often expose modeling and analysis shortcomings. Algorithm engineering touches other research areas such as algorithm theory, combinatorial optimization, computer architecture, parallel and distributed computing, high-performance computing, and operations research. Prominent success stories in algorithm engineering include the linear program solver CPLEX, the traveling salesman suite CONCORDE, speed-up techniques for shortest paths computation, for example, in route planning, as well as graph partitioning and the computation of Steiner trees. All these topics are driven by the need for efficient algorithms and libraries for problems that appear frequently in real-world applications. In the last fifteen years, this approach to algorithmic research has gained increasing attention. There is an ACM Journal on Experimental Algorithmics and several annual conferences (WAE/ESA applied track since 1997, Alenex since 1998, and WEA/SEA since 2001) and the series of DIMACS implementation challenges where people meet to compare implementations for a specific problem. From 2007 to 2013 the German Research Foundation also funded a special priority program on algorithm engineering (DFG SPP 1307).

Cite as

Andrew V. Goldberg, Giuseppe F. Italiano, David S. Johnson, and Dorothea Wagner. Algorithm Engineering (Dagstuhl Seminar 13391). In Dagstuhl Reports, Volume 3, Issue 9, pp. 169-189, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@Article{goldberg_et_al:DagRep.3.9.169,
  author =	{Goldberg, Andrew V. and Italiano, Giuseppe F. and Johnson, David S. and Wagner, Dorothea},
  title =	{{Algorithm Engineering (Dagstuhl Seminar 13391)}},
  pages =	{169--189},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{3},
  number =	{9},
  editor =	{Goldberg, Andrew V. and Italiano, Giuseppe F. and Johnson, David S. and Wagner, Dorothea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.3.9.169},
  URN =		{urn:nbn:de:0030-drops-44214},
  doi =		{10.4230/DagRep.3.9.169},
  annote =	{Keywords: Algorithm Engineering, Science of Algorithmics, Manycore Algorithms, Certifying Algorithms, Web Search, Large Graphs}
}
Document
10261 Abstracts Collection – Algorithm Engineering

Authors: Giuseppe F. Italiano, David S. Johnson, Petra Mutzel, and Peter Sanders

Published in: Dagstuhl Seminar Proceedings, Volume 10261, Algorithm Engineering (2010)


Abstract
From June 27 to July 2, the Dagstuhl Seminar 10261 ``Algorithm Engineering '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

Cite as

Giuseppe F. Italiano, David S. Johnson, Petra Mutzel, and Peter Sanders. 10261 Abstracts Collection – Algorithm Engineering. In Algorithm Engineering. Dagstuhl Seminar Proceedings, Volume 10261, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{italiano_et_al:DagSemProc.10261.1,
  author =	{Italiano, Giuseppe F. and Johnson, David S. and Mutzel, Petra and Sanders, Peter},
  title =	{{10261 Abstracts Collection – Algorithm Engineering}},
  booktitle =	{Algorithm Engineering},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10261},
  editor =	{Giuseppe F. Italiano and David S. Johnson and Petra Mutzel and Peter Sanders},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10261.1},
  URN =		{urn:nbn:de:0030-drops-28179},
  doi =		{10.4230/DagSemProc.10261.1},
  annote =	{Keywords: Experimental algorithmics, Game theory, Parallel and distributed algorithms, Multi-core}
}
Document
10261 Executive Summary – Algorithm Engineering

Authors: Giuseppe F. Italiano, David S. Johnson, Petra Mutzel, and Peter Sanders

Published in: Dagstuhl Seminar Proceedings, Volume 10261, Algorithm Engineering (2010)


Abstract
Algorithm engineering (AE) consists of the design, theoretical analysis, implementation, and experimental evaluation of algorithms, with the aim of bridging the gap between theory and practice in the area of algorithms. In the last decade, this approach to algorithmic research has gained increasing attention. The aim of this seminar was to bring together researchers with different backgrounds, e.g., from combinatorial optimization, algorithmic theory, and algorithm engineering, in order to strengthen and foster collaborations in the area of algorithm engineering and to identify key research directions for the future.

Cite as

Giuseppe F. Italiano, David S. Johnson, Petra Mutzel, and Peter Sanders. 10261 Executive Summary – Algorithm Engineering. In Algorithm Engineering. Dagstuhl Seminar Proceedings, Volume 10261, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{italiano_et_al:DagSemProc.10261.2,
  author =	{Italiano, Giuseppe F. and Johnson, David S. and Mutzel, Petra and Sanders, Peter},
  title =	{{10261 Executive Summary – Algorithm Engineering}},
  booktitle =	{Algorithm Engineering},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10261},
  editor =	{Giuseppe F. Italiano and David S. Johnson and Petra Mutzel and Peter Sanders},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10261.2},
  URN =		{urn:nbn:de:0030-drops-27966},
  doi =		{10.4230/DagSemProc.10261.2},
  annote =	{Keywords: Experimental algorithmics, Game theory, Parallel and distributed algorithms, Multi-core}
}
Document
An Experimental Comparison of Speed Scaling Algorithms with Deadline Feasibility Constraints

Authors: Ahmed Abousamra, David P. Bunde, and Kirk Pruhs

Published in: Dagstuhl Seminar Proceedings, Volume 10261, Algorithm Engineering (2010)


Abstract
We consider the first, and most well studied, speed scaling problem in the algorithmic literature: where the scheduling quality of service measure is a deadline feasibility constraint, and where the power objective is to minimize the total energy used. Four online algorithms for this problem have been proposed in the algorithmic literature. Based on the best upper bound that can be proved on the competitive ratio, the ranking of the online algorithms from best to worst is: $qOA$, $OA$, $AVR$, $BKP$. As a test case on the effectiveness of competitive analysis to predict the best online algorithm, we report on an experimental ``horse race'' between these algorithms using instances based on web server traces. Our main conclusion is that the ranking of our algorithms based on their performance in our experiments is identical to the order predicted by competitive analysis. This ranking holds over a large range of possible power functions, and even if the power objective is temperature.

Cite as

Ahmed Abousamra, David P. Bunde, and Kirk Pruhs. An Experimental Comparison of Speed Scaling Algorithms with Deadline Feasibility Constraints. In Algorithm Engineering. Dagstuhl Seminar Proceedings, Volume 10261, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{abousamra_et_al:DagSemProc.10261.3,
  author =	{Abousamra, Ahmed and Bunde, David P. and Pruhs, Kirk},
  title =	{{An Experimental Comparison of Speed Scaling Algorithms with Deadline Feasibility Constraints}},
  booktitle =	{Algorithm Engineering},
  pages =	{1--22},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10261},
  editor =	{Giuseppe F. Italiano and David S. Johnson and Petra Mutzel and Peter Sanders},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10261.3},
  URN =		{urn:nbn:de:0030-drops-27971},
  doi =		{10.4230/DagSemProc.10261.3},
  annote =	{Keywords: Scheduling, Speed Scaling, Experimental Algorithms, Power Management}
}
Document
On Dynamic Graph Partitioning and Graph Clustering using Diffusion

Authors: Henning Meyerhenke and Joachim Gehweiler

Published in: Dagstuhl Seminar Proceedings, Volume 10261, Algorithm Engineering (2010)


Abstract
Load balancing is an important requirement for the efficient execution of parallel numerical simulations. In particular when the simulation domain changes over time, the mapping of computational tasks to processors needs to be modified accordingly. State-of-the-art libraries for this problem are based on graph repartitioning. They have a number of drawbacks, including the optimized metric and the difficulty of parallelizing the popular repartitioning heuristic Kernighan-Lin (KL). Here we further explore the very promising diffusion-based graph partitioning algorithm DIBAP (Meyerhenke et al., JPDC 69(9):750–761, 2009) by adapting DIBAP to the related problem of load balancing. The presented experiments with graph sequences that imitate adaptive numerical simulations demonstrate the applicability and high quality of DIBAP for load balancing by repartitioning. Compared to the faster state-of-the-art repartitioners PARMETIS and parallel JOSTLE, DIBAP’s solutions have partitions with significantly fewer external edges and boundary nodes and the resulting average migration volume in the important maximum norm is also the best in most cases. We also prove that one of DIBAP's key components optimizes a relaxed version of the minimum edge cut problem. Moreover, we hint at a distributed algorithm based on ideas used in DIBAP for clustering a virtual P2P supercomputer.

Cite as

Henning Meyerhenke and Joachim Gehweiler. On Dynamic Graph Partitioning and Graph Clustering using Diffusion. In Algorithm Engineering. Dagstuhl Seminar Proceedings, Volume 10261, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{meyerhenke_et_al:DagSemProc.10261.4,
  author =	{Meyerhenke, Henning and Gehweiler, Joachim},
  title =	{{On Dynamic Graph Partitioning and Graph Clustering using Diffusion}},
  booktitle =	{Algorithm Engineering},
  pages =	{1--19},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10261},
  editor =	{Giuseppe F. Italiano and David S. Johnson and Petra Mutzel and Peter Sanders},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.10261.4},
  URN =		{urn:nbn:de:0030-drops-27980},
  doi =		{10.4230/DagSemProc.10261.4},
  annote =	{Keywords: Dynamic graph partitioning/clustering, disturbed diffusion, load balancing, relaxed cut optimization}
}
Document
The Travelling Salesman Problem (Dagstuhl Seminar 02261)

Authors: David S. Johnson, Jan Karel Lenstra, and Gerhard J. Woeginger

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


Abstract

Cite as

David S. Johnson, Jan Karel Lenstra, and Gerhard J. Woeginger. The Travelling Salesman Problem (Dagstuhl Seminar 02261). Dagstuhl Seminar Report 346, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2004)


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@TechReport{johnson_et_al:DagSemRep.346,
  author =	{Johnson, David S. and Lenstra, Jan Karel and Woeginger, Gerhard J.},
  title =	{{The Travelling Salesman Problem (Dagstuhl Seminar 02261)}},
  pages =	{1--17},
  ISSN =	{1619-0203},
  year =	{2004},
  type = 	{Dagstuhl Seminar Report},
  number =	{346},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemRep.346},
  URN =		{urn:nbn:de:0030-drops-152271},
  doi =		{10.4230/DagSemRep.346},
}
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