SkyAlign: a portable, work-efficient skyline algorithm for multicore and GPU architectures

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  • Kenneth Sejdenfaden Bøgh
  • ,
  • Sean Chester, Norwegian University of Science and Technology (NTNU), Trondheim,
  • Ira Assent
The skyline operator determines points in a multidimensional dataset that offer some optimal trade-off. State-of-the-art CPU skyline algorithms exploit quad-tree partitioning with complex branching to minimise the number of point-to-point comparisons. Branch-phobic GPU skyline algorithms rely on compute throughput rather than partitioning, but fail to match the performance of sequential algorithms. In this paper, we introduce a new skyline algorithm, SkyAlign, that is designed for the GPU, and a GPU-friendly, grid-based tree structure upon which the algorithm relies. The search tree allows us to dramatically reduce the amount of work done by the GPU algorithm by avoiding most point-to-point comparisons at the cost of some compute throughput. This trade-off allows SkyAlign to achieve orders of magnitude faster performance than its predecessors. Moreover, a NUMA-oblivious port of SkyAlign outperforms native multicore state of the art on challenging workloads by an increasing margin as more cores and sockets are utilised.
Original languageEnglish
JournalThe VLDB Journal
Volume25
Issue6
Pages (from-to)817-841
Number of pages25
ISSN1066-8888
DOIs
Publication statusPublished - Dec 2016

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