Parallel mesh partitioning based on space filling curves

R. Borrell, J. C. Cajas, D. Mira, A. Taha, S. Koric, M. Vázquez, G. Houzeaux

Research output: Contribution to journalArticlepeer-review


Larger supercomputers allow the simulation of more complex phenomena with increased accuracy. Eventually this requires finer and thus also larger geometric discretizations. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, deformation, adaptation/regeneration or partition/load balance, become a critical issue within the simulation workflow. In this paper we focus on mesh partitioning. In particular, we present a fast and scalable geometric partitioner based on Space Filling Curves (SFC), as an alternative to the standard graph partitioning approach. We have avoided any computing or memory bottleneck in the algorithm, while we have imposed that the solution achieved is independent (discounting rounding off errors) of the number of parallel processes used to compute it. The performance of the SFC-based partitioner presented has been demonstrated using up to 4096 CPU-cores in the Blue Waters supercomputer.

Original languageEnglish (US)
Pages (from-to)264-272
Number of pages9
JournalComputers and Fluids
StatePublished - Sep 15 2018


  • Geometric partitioning
  • Mesh partitioning
  • Parallel computing
  • SFC
  • Space filling curve

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering


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