Aquila-LCS: GPU/CPU-accelerated particle advection schemes for large-scale simulations

We introduce Aquila-LCS, GPU and CPU optimized object-oriented, in-house codes for volumetric particle advection and 3D Finite-Time Lyapunov Exponent (FTLE) and Finite-Size Lyapunov Exponent (FSLE) computations. The purpose is to analyze 3D Lagrangian Coherent Structures (LCS) in large Direct Numeri...

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Veröffentlicht in:SoftwareX Jg. 27; S. 101836
Hauptverfasser: Lagares, Christian, Araya, Guillermo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.09.2024
Elsevier
Schlagworte:
Distributed memory algorithms
DNS
FSLE
FTLE
GPU-accelerated
LCS
DNS
GPU-accelerated
LCS
Distributed memory algorithms
FTLE
FSLE
ISSN:2352-7110, 2352-7110
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Beschreibung
Zusammenfassung:We introduce Aquila-LCS, GPU and CPU optimized object-oriented, in-house codes for volumetric particle advection and 3D Finite-Time Lyapunov Exponent (FTLE) and Finite-Size Lyapunov Exponent (FSLE) computations. The purpose is to analyze 3D Lagrangian Coherent Structures (LCS) in large Direct Numerical Simulation (DNS) data. Our technique uses advanced search strategies for quick cell identification and efficient storage techniques. This solver scales effectively on both GPUs (up to 62 NVIDIA V100 GPUs) and multi-core CPUs (up to 32,768 CPU-cores), tracking up to 8-billion particles. We apply our approach to turbulent boundary layers at different flow regimes and Reynolds numbers.
ISSN:2352-7110
2352-7110
DOI:10.1016/j.softx.2024.101836