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Improving Hash Distributed A* for Shared Memory Architectures Using Abstraction

  • Victoria Sanz
  • Armando De Giusti
  • Marcelo Naiouf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10048)

Abstract

The A* algorithm is generally used to solve combinatorial optimization problems, but it requires high computing power and a large amount of memory, hence, efficient parallel A* algorithms are needed. In this sense, Hash Distributed A* (HDA*) parallelizes A* by applying a decentralized strategy and a hash-based node distribution scheme. However, this distribution scheme results in frequent node transfers among processors. In this paper, we present Optimized AHDA*, a version of HDA* for shared memory architectures, that uses an abstraction-based node distribution scheme and a technique to group several nodes before transferring them to the corresponding thread. Both methods reduce the amount of node transfers and mitigate communication and contention. We assess the effect of each technique on algorithm performance. Finally, we evaluate the scalability of the proposed algorithm, when it is run on a multicore machine, using the 15-puzzle as a case study.

Keywords

HDA* for shared memory architectures Abstraction-based node distribution scheme Hash-based node distribution scheme Scalability Combinatorial optimization problems 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Victoria Sanz
    • 1
    • 2
  • Armando De Giusti
    • 1
    • 2
  • Marcelo Naiouf
    • 1
  1. 1.III-LIDI, School of Computer SciencesNational University of La PlataLa PlataArgentina
  2. 2.CONICET, Ministry of Science, Technology and Productive InnovationBuenos AiresArgentina

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