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Efficient GPU-based skyline computation

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Kenneth Sejdenfaden Bøgh, Denmark
  • Ira Assent
  • Matteo Magnani, Denmark
The skyline operator for multi-criteria search returns the most interesting points of a data set with respect to any monotone preference function. Existing work has almost exclusively focused on efficiently computing skylines on one or more CPUs, ignoring the high parallelism possible in GPUs. In this paper we investigate the challenges for efficient skyline algorithms that exploit the computational power of the GPU. We present a novel strategy for managing data transfer and memory for skylines using CPU and GPU. Our new sorting based data-parallel skyline algorithm is introduced and its properties are discussed. We demonstrate in a thorough experimental evaluation that this algorithm is faster than state-of-the-art sequential sorting based skyline algorithms and that it shows superior scalability.
Original languageEnglish
Title of host publicationProceedings of the Ninth International Workshop on Data Management on New Hardware , DaMoN '13
EditorsRyan Johnson, Alfons Kemper
Number of pages6
PublisherAssociation for Computing Machinery
Publication year2013
Article number5
ISBN (Electronic)978-1-4503-2196-9
Publication statusPublished - 2013
EventInternational Workshop on Data Management on New Hardware - New York, United States
Duration: 22 Jun 201327 Jun 2013
Conference number: 9


ConferenceInternational Workshop on Data Management on New Hardware
LandUnited States
ByNew York

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