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  • 标题:In-Place Parallel Super Scalar Samplesort (IPSSSSo)
  • 本地全文:下载
  • 作者:Michael Axtmann ; Sascha Witt ; Daniel Ferizovic
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2017
  • 卷号:87
  • 页码:9:1-9:14
  • DOI:10.4230/LIPIcs.ESA.2017.9
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:We present a sorting algorithm that works in-place, executes in parallel, is cache-efficient, avoids branch-mispredictions, and performs work O(n log n) for arbitrary inputs with high probability. The main algorithmic contributions are new ways to make distribution-based algorithms in-place: On the practical side, by using coarse-grained block-based permutations, and on the theoretical side, we show how to eliminate the recursion stack. Extensive experiments shw that our algorithm IPSSSSo scales well on a variety of multi-core machines. We outperform our closest in-place competitor by a factor of up to 3. Even as a sequential algorithm, we are up to 1.5 times faster than the closest sequential competitor, BlockQuicksort.
  • 关键词:shared memory; parallel sorting; in-place algorithm; comparison-based sorting; branch prediction
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