Exploiting GPUs in Solving (Distributed) Constraint Optimization Problems with Dynamic Programming

  • Ferdinando FiorettoEmail author
  • Tiep Le
  • Enrico Pontelli
  • William Yeoh
  • Tran Cao Son
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9255)


This paper proposes the design and implementation of a dynamic programming based algorithm for (distributed) constraint optimization, which exploits modern massively parallel architectures, such as those found in modern Graphical Processing Units (GPUs). The paper studies the proposed algorithm in both centralized and distributed optimization contexts. The experimental analysis, performed on unstructured and structured graphs, shows the advantages of employing GPUs, resulting in enhanced performances and scalability.


Multiagent System Global Memory Constraint Graph Constraint Optimization Problem Distribute Constraint Optimization Problem 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Ferdinando Fioretto
    • 1
    • 2
    Email author
  • Tiep Le
    • 1
  • Enrico Pontelli
    • 1
  • William Yeoh
    • 1
  • Tran Cao Son
    • 1
  1. 1.Department of Computer ScienceNew Mexico State UniversityLas CrucesUSA
  2. 2.Department of Mathematics and Computer ScienceUniversity of UdineUdineItaly

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