Efficiency of particle search methods in smoothed particle hydrodynamics: a comparative study (part I)

E. Plaza*, Leonardo G. Di Sigalotti, Luis Pérez, Jorge Troconis, Wilfredo Angulo, María Castro

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Nearest neighbour searching is central to the efficiency of smoothed particle hydrodynamics (SPH). Here the performance of the brute force (BF) or direct search (DS), the cell-linked list (CLL), and the KD-tree (KDT) methods in vectorised form are analysed. The results indicate that the efficiency of the SPH calculations is improved with the vectorised cell-linked list (VCLL) and the vectorised KD-tree (VKDT). However, the VKDT approach is more efficient than the VCLL method for N ≤ 105 in two dimensions (2D) and N ≤ 106 in three dimensions (3D). For larger N, the time duration of the SPH calculations with the VKDT method grows steeply while a linear trend is maintained with the VCLL. The complexity here is measured not only for early events but also close to the point of hardware limit, in which the complexity has a different behaviour, which can be measured and compared using a power fit.

Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalProgress in Computational Fluid Dynamics
Volume21
Issue number1
DOIs
StatePublished - 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2021 Inderscience Enterprises Ltd.

Keywords

  • Closest pair search
  • Data structures
  • Nearest neighbour search
  • Smoothed particle hydrodynamics
  • SPH

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