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Better algorithms for parallel backtracking

  • Peter Sanders
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 980)

Abstract

Many algorithms in operations research and artificial intelligence are based on the backtracking principle, i.e., depth first search in implicitly defined trees. For parallelizing these algorithms, an efficient load balancing scheme is of central importance.

Previously known load balancing algorithms either require sending a message for each tree node or they only work efficiently for large search trees. This paper introduces new randomized dynamic load balancing algorithms for tree structured computations, a generalization of backtrack search. These algorithms only need to communicate when necessary and have an asymptotically optimal scalability for hypercubes, butterflies and related networks, and an improved scalability for meshes and hierarchical networks like fat trees.

Keywords

Analysis of randomized algorithms depth first search distributed memory divide and conquer load balancing parallel backtracking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Peter Sanders
    • 1
  1. 1.University of KarlsruheKarlsruheGermany

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