Sorting a set of items is a task that can be useful by itself or as a building block for more complex operations. That is why a lot of effort has been put into finding sorting algorithms that sort large sets as efficiently as possible. But the more sophisticated and complex the algorithms become, the less efficient they are for small sets of items due to large constant factors. A relatively simple sorting algorithm that is often used as a base case sorter is insertion sort, because it has small code size and small constant factors influencing its execution time. We aim to determine if there is a faster way to sort small sets of items to provide an efficient base case sorter. We looked at sorting networks, at how they can improve the speed of sorting few elements, and how to implement them in an efficient manner using conditional moves. Since sorting networks need to be implemented explicitly for each set size, providing networks for larger sizes becomes less efficient due to increased code sizes. To also enable the sorting of slightly larger base cases, we adapted sample sort to Register Sample Sort, to break down those larger sets into sizes that can in turn be sorted by sorting networks. ... mehr

Zugehörige Institution(en) am KIT |
Institut für Theoretische Informatik (ITI) |

Publikationstyp |
Zeitschriftenaufsatz |

Publikationsjahr |
2020 |

Sprache |
Englisch |

Identifikator |
ISSN: 0038-0644, 1097-024X KITopen-ID: 1000127671 |

Erschienen in |
Software <Chichester> |

Verlag |
Wiley |

Vorab online veröffentlicht am |
02.11.2020 |

Schlagwörter |
base case sorting, sample sort, sorter, sorting, sorting algorithm, sorting networks |

Nachgewiesen in |
Scopus Web of Science |

Relationen in KITopen |

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