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Article Dans Une Revue Computer Physics Communications Année : 2022

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

Résumé

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.
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Dates et versions

hal-03682460 , version 1 (31-05-2022)

Identifiants

Citer

Cristian Lalescu, Bérenger Bramas, Markus Rampp, Michael Wilczek. An efficient particle tracking algorithm for large-scale parallel pseudo-spectral simulations of turbulence. Computer Physics Communications, 2022, 278, pp.108406. ⟨10.1016/j.cpc.2022.108406⟩. ⟨hal-03682460⟩
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