Randomized range-maxima in nearly-constant parallel time

Extended abstract
  • Omer Berkman
  • Yossi Matias
  • Uzi Vishkin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 650)


Given an array of n input numbers, the range-maxima problem is to preprocess the data so that queries of the type “what is the maximum value in subarray [i..j]” can be answered quickly using one processor. We present a randomized preprocessing algorithm that runs in O(log*n) time with high probability, using an optimal number of processors on a CRCW PRAM; each query can be processed in constant time by one processor. We also present a randomized algorithm for a parallel comparison model. Using an optimal number of processors, the preprocessing algorithm runs in O(α(n)) time with high probability; each query can be processed in O(α(n)) time by one processor. (α(n) is the inverse of Ackermann function.) A constant time query can be achieved by some slowdown in the performance of the preprocessing stage.


Constant Time Maximum Computation Complete Binary Tree Lower Common Ancestor Preprocessing Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Omer Berkman
    • 1
  • Yossi Matias
    • 2
  • Uzi Vishkin
    • 1
  1. 1.Dept. of Computing, School of Physical Sciences and EngineeringKing's College LondonStrand, LondonEngland
  2. 2.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

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