基于gpu的非均匀网格压缩晶格Boltzmann模拟使用标准c++并行:从最佳实践到空气动力学,空气声学和超音速流动模拟

IF 3.4 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Christophe Coreixas , Jonas Latt
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引用次数: 0

摘要

尽管经过数十年的研究,在非均匀网格上创建精确、鲁棒和高效的晶格玻尔兹曼方法(LBM)仍然具有挑战性。这项工作引入了一种新的策略,通过集成简单而有效的组件来解决这一挑战:(1)现代c++中的并行算法,(2)保守的以细胞为中心的网格优化,(3)局部边界条件,(4)鲁棒碰撞模型。我们的框架支持多个格(D2Q9, D2Q13, D2Q21, D2Q37, D3Q27等)量身定制的各种流动条件。它包括具有多项式和数值平衡的碰撞模型,多原子行为的第二分布,类似詹姆斯的冲击传感器,并推广了罗德的改进策略。该框架的准确性和鲁棒性在不同的基准测试中得到了验证,包括盖驱动的腔体流动、风噪声、30P30N翼型空气动力学、无粘黎曼问题,以及在跨声速和超音速状态下通过NACA翼型的粘性流动。现代c++进一步使我们的框架能够达到gpu原生性能,同时确保高可移植性、模块化和易于实现。值得注意的是,弱可压缩lbm在非均匀网格上实现了最先进的GPU效率,而完全可压缩lbm在大多数计算密集型情况下受益于相当于数千个CPU内核的加速。我们先进的性能模型结合了邻居列表和异步时间步进效应,为非均匀网格上LB模拟的性能分解提供了新的见解。总的来说,该研究为便携式树基lbm设定了新的标准,证明了精心选择的组件组合可以在各种流动条件下实现高性能、准确性和鲁棒性。作为最后的概念验证,提出了亚音速和超音速应用的自适应网格细化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU-based compressible lattice Boltzmann simulations on non-uniform grids using standard C++ parallelism: From best practices to aerodynamics, aeroacoustics and supersonic flow simulations
Despite decades of research, creating accurate, robust, and efficient lattice Boltzmann methods (LBM) on non-uniform grids with seamless GPU acceleration remains challenging. This work introduces a novel strategy to address this challenge by integrating simple yet effective components: (1) parallel algorithms in modern C++, (2) conservative cell-centered grid refinement, (3) local boundary conditions, and (4) robust collision models. Our framework supports multiple lattices (D2Q9, D2Q13, D2Q21, D2Q37, D3Q27, etc) tailored to various flow conditions. It includes collision models with polynomial and numerical equilibria, a second distribution for polyatomic behavior, a Jameson-like shock sensor, and generalizes Rohde's refinement strategy.
The framework's accuracy and robustness is validated across diverse benchmarks, including lid-driven cavity flows, Aeolian noise, 30P30N airfoil aerodynamics, inviscid Riemann problems, and viscous flows past a NACA airfoil in transonic and supersonic regimes. Modern C++ further enables our framework to reach GPU-native performance, while ensuring high portability, modularity, and ease of implementation. Notably, weakly compressible LBMs achieve state-of-the-art GPU efficiency on non-uniform grids, while fully compressible LBMs benefit from acceleration equivalent to thousands of CPU cores in the most compute-intensive cases. Our advanced performance models incorporate neighbor-list and asynchronous time-stepping effects, providing new insights into the performance decomposition of LB simulations on non-uniform grids.
Overall, this study sets a new standard for portable, tree-based LBMs, demonstrating that a combination of well-chosen components can achieve high performance, accuracy, and robustness across various flow conditions. As a final proof-of-concept, adaptive mesh refinement is proposed for subsonic and supersonic applications.
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来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
期刊介绍: The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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