An Efficient Particle Tracking Algorithm for LargeScale Parallel PseudoSpectral Simulations of Turbulence
Abstract
Particle tracking in largescale 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 largescale parallel pseudospectral simulations of turbulence which scales well up to billions of tracer particles on modern highperformance 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 interprocess communication required by particle tracking, we introduce a taskbased approach to overlap pointtopoint 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.
 Publication:

arXiv eprints
 Pub Date:
 July 2021
 arXiv:
 arXiv:2107.01104
 Bibcode:
 2021arXiv210701104L
 Keywords:

 Physics  Fluid Dynamics;
 Computer Science  Distributed;
 Parallel;
 and Cluster Computing;
 Physics  Computational Physics