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Efficient GPU-based skyline computation
Aarhus University.
Aarhus University.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (UDBL)
2013 (English)In: Proceedings of the Ninth International Workshop on Data Management on New Hardware (DaMoN @ SIGMOD), 2013Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2013.
National Category
Information Systems
Identifiers
URN: urn:nbn:se:uu:diva-204588DOI: 10.1145/2485278.2485283ISBN: 978-1-4503-2196-9 (print)OAI: oai:DiVA.org:uu-204588DiVA: diva2:640596
Conference
SIGMOD
Available from: 2013-08-14 Created: 2013-08-06 Last updated: 2013-12-10

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Publisher's full texthttp://dl.acm.org/citation.cfm?id=2485283

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Magnani, Matteo

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