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Improving the Cache-Efficiency of Shortest Path Search

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KI 2017: Advances in Artificial Intelligence (KI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10505))

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Abstract

Flood-filling algorithms as used for coloring images and shadow casting show that improved locality greatly increases the cache performance and, in turn, reduces the running time of an algorithm. In this paper we look at Dijkstra’s method to compute the shortest paths for example to generate pattern databases. As cache-improving contributions, we propose edge-cost factorization and flood-filling the memory layout of the graph. We conduct experiments in commercial game maps and compare the new priority queues with advanced heap implementations as well as and with alternative bucket implementations.

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Author information

Authors and Affiliations

  1. King’s College London, London, UK

    Stefan Edelkamp

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  1. Stefan Edelkamp
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Correspondence to Stefan Edelkamp .

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Editors and Affiliations

  1. Fakultät für Informatik, Technische Universität Dortmund, Dortmund, Germany

    Gabriele Kern-Isberner

  2. FB Informatik, TU Darmstadt, Darmstadt, Hessen, Germany

    Johannes Fürnkranz

  3. FB Informatik, Universität Koblenz, Koblenz, Rheinland-Pfalz, Germany

    Matthias Thimm

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Edelkamp, S. (2017). Improving the Cache-Efficiency of Shortest Path Search. In: Kern-Isberner, G., Fürnkranz, J., Thimm, M. (eds) KI 2017: Advances in Artificial Intelligence. KI 2017. Lecture Notes in Computer Science(), vol 10505. Springer, Cham. https://doi.org/10.1007/978-3-319-67190-1_8

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  • DOI: https://doi.org/10.1007/978-3-319-67190-1_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67189-5

  • Online ISBN: 978-3-319-67190-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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