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

被引：0

作者：

Lagares, Christian ^{[1
,2
]}

Araya, Guillermo ^{[2
]}

机构：

[1] Univ Puerto Rico, Dept Mech Eng, POB 9000, Mayaguez, PR 00681 USA

[2] Univ Texas San Antonio, Dept Mech Eng, Computat Turbulence & Visualizat Lab, San Antonio, TX 78249 USA

来源：

SOFTWAREX | 2024年 / 27卷

关键词：

LCS; GPU-accelerated; DNS; Distributed memory algorithms; FTLE; FSLE; LAGRANGIAN COHERENT STRUCTURES; COMPUTATION; FTLE;

D O I：

10.1016/j.softx.2024.101836

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页数：7

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