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Jaya optimization algorithm with GPU acceleration

  • A. Jimeno-Morenilla
  • J. L. Sánchez-Romero
  • H. Migallón
  • H. Mora-Mora
Article
  • 118 Downloads

Abstract

Optimization methods allow looking for an optimal value given a specific function within a constrained or unconstrained domain. These methods are useful for a wide range of scientific and engineering applications. Recently, a new optimization method called Jaya has generated growing interest because of its simplicity and efficiency. In this paper, we present the Jaya GPU-based parallel algorithms we developed and analyze both parallel performance and optimization performance using a well-known benchmark of unconstrained functions. Results indicate that parallel Jaya implementation achieves significant speed-up for all benchmark functions, obtaining speed-ups of up to \(190\times \), without affecting optimization performance.

Keywords

Jaya Optimization Parallelism GPU CUDA 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer TechnologyUniversity of AlicanteAlicanteSpain
  2. 2.Department of Physics and Computer ArchitectureMiguel Hernández UniversityElcheSpain

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