• DocumentCode
    2707525
  • Title

    The performance of linear time suffix sorting algorithms

  • Author

    Puglisi, Simon J. ; Smyth, William F. ; Turpin, Andrew

  • Author_Institution
    Dept. of Comput., Curtin Univ. of Technol., Perth, WA, Australia
  • fYear
    2005
  • fDate
    29-31 March 2005
  • Firstpage
    358
  • Lastpage
    367
  • Abstract
    We have illustrated that the superior asymptotic complexity of linear time suffix sorting algorithms does not readily translate into faster suffix sorting, compared to implementations of supralinear algorithms. We have also resolved the ambiguity surrounding the practicality of the Algorithm KA: it is slower than supralinear approaches on real data. We described several optimizations to the O(n) KS algorithm that significantly improve performance for real world inputs, but still fall short of some supralinear approaches. It is worth noting that most of the optimizations we describe could also be applied to Algorithm KB, which may then outperform the well tuned suffix sorter of Manzini and Ferragina (2004).
  • Keywords
    computational complexity; data compression; optimisation; software performance evaluation; sorting; Algorithm KA; Algorithm KB; KS algorithm; asymptotic complexity; linear time suffix sorting algorithms; lossless compression; optimizations; performance; supralinear algorithms; Australia; Computer science; Councils; Data compression; Indexing; Software algorithms; Software engineering; Sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 2005. Proceedings. DCC 2005
  • ISSN
    1068-0314
  • Print_ISBN
    0-7695-2309-9
  • Type

    conf

  • DOI
    10.1109/DCC.2005.87
  • Filename
    1402197