A Probabilistic Pipeline Algorithm for K Selection on the Tree Machine

  • Authors:
  • Albert G. Greenberg;Udi Manber

  • Affiliations:
  • AT&T Bell Laboratories, Murray Hill, NJ;Univ. of Wisconsin, Madison

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1987

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Abstract

We consider the problem of selecting the kth largest of n inputs, where initially the inputs are stored in the n leaf processors of the 2n - 1 processor tree machine. A probabilistic algorithm is presented that implements a type of pipelining to solve the problem in a simple data driven fashion, with each processor maintaining just a constant amount of state information. On any problem instance, t