Nested OpenMP for efficient computation of 3D critical points in multi-block CFD datasets

ABSTRACT

Extraction of complex data structures like vector field topologies in large-scale, unsteady flow field datasets for the interactive exploration in virtual environments cannot be carried out without parallelization strategies. We present an approach based on Nested OpenMP to find critical points, which are the essential parts of velocity field topologies. We evaluate our parallelization scheme on several multi-block datasets, and present the results for various thread counts and loop schedules on all parallelization levels. Our experience suggests that upcoming massively multi-threaded processor architectures can be very advantageously for large-scale feature extractions.

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INDEX TERMS

Primary Classification:
  D. Software
  D.1 PROGRAMMING TECHNIQUES
      D.1.3 Concurrent Programming
          Subjects: Parallel programming

Additional Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.3 Language Constructs and Features
          Subjects: Concurrent programming structures

  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.2 Graphics Systems
          Subjects: Distributed/network graphics
      I.3.7 Three-Dimensional Graphics and Realism

General Terms:
Design, Theory

Keywords:
CFD post-processing, flow field topology, multi-threading, nested parallelization, virtual reality