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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Bibliographic Details
Published in:	SoftwareX Vol. 27; p. 101836
Main Authors:	Lagares, Christian, Araya, Guillermo
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.09.2024 Elsevier
Subjects:	Distributed memory algorithms DNS FSLE FTLE GPU-accelerated LCS DNS GPU-accelerated LCS Distributed memory algorithms FTLE FSLE
ISSN:	2352-7110, 2352-7110
Online Access:	Get full text
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Summary:	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