• DocumentCode
    770845
  • Title

    Tree-lookup for partial sums or: how can I find this stuff quickly?

  • Author

    Beichl, Isabel ; Sullivan, Francis

  • Author_Institution
    Comput. & Appl. Math. Lab., US Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
  • Volume
    3
  • Issue
    1
  • fYear
    1996
  • Firstpage
    13
  • Lastpage
    15
  • Abstract
    Suppose that you need to maintain a large list of data that is to be searched and modified frequently in the course of a computation. You can almost always arrange for both operations to be done efficiently by storing the data in a structure other than a single array. Although there are several elegant ways to do this, we present just one: a simple tree that doesn´t require a lot of thinking to implement. It can speed up execution tremendously because instead of searching through a list item after item for each update, possibly examining n items, you need only examine O(log n) items per operation. (More advanced methods can reduce this to log*n at the cost of more complex programming. Here, log*n is the number of iterations of log2 that are required to get below 1. For numbers having less than 65K bits, log* is less than 5.)
  • Keywords
    information retrieval; list processing; table lookup; tree searching; data searching; data structure; iterations; large data list; partial sums; simple tree; tree lookup; Binary trees; Costs; Data structures; Epitaxial growth; Molecular beam epitaxial growth; Monte Carlo methods; Physics computing; Random number generation; Springs;
  • fLanguage
    English
  • Journal_Title
    Computational Science & Engineering, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9924
  • Type

    jour

  • DOI
    10.1109/99.486756
  • Filename
    486756