An efficient particle tracking algorithm for large-scale parallel pseudo-spectral simulations of turbulence

Particle tracking in large-scale numerical simulations of turbulent flows presents one of the major bottlenecks in parallel performance and scaling efficiency. Here, we describe a particle tracking algorithm for large-scale parallel pseudo-spectral simulations of turbulence which scales well up to b...

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Veröffentlicht in:Computer physics communications Jg. 278; S. 108406
Hauptverfasser: Lalescu, Cristian C., Bramas, Bérenger, Rampp, Markus, Wilczek, Michael
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.09.2022
Elsevier
Schlagworte:
Computer Science
Distributed, Parallel, and Cluster Computing
MPI
OpenMP
Particle tracking
Turbulence simulations
Turbulence simulations
OpenMP
Particle tracking
MPI
ISSN:0010-4655, 1879-2944
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Zusammenfassung:Particle tracking in large-scale numerical simulations of turbulent flows presents one of the major bottlenecks in parallel performance and scaling efficiency. Here, we describe a particle tracking algorithm for large-scale parallel pseudo-spectral simulations of turbulence which scales well up to billions of tracer particles on modern high-performance computing architectures. We summarize the standard parallel methods used to solve the fluid equations in our hybrid MPI/OpenMP implementation. As the main focus, we describe the implementation of the particle tracking algorithm and document its computational performance. To address the extensive inter-process communication required by particle tracking, we introduce a task-based approach to overlap point-to-point communications with computations, thereby enabling improved resource utilization. We characterize the computational cost as a function of the number of particles tracked and compare it with the flow field computation, showing that the cost of particle tracking is very small for typical applications.
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2022.108406