基于AMR的计算流体动力学代码移植到大规模GPU平台

J. H. Davis, Justin Shafner, Daniel Nichols, N. Grube, P. Martin, A. Bhatele
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引用次数: 0

摘要

高超声速湍流流动的精确建模具有巨大的科学和商业价值,适用于大气飞行、超声速燃烧、材料发现和气候预测。在本文中,我们描述了我们在扩展CRoCCo的功能和现代化方面的经验,CRoCCo是一个基于mpi的,仅cpu可压缩的计算流体动力学代码。我们扩展了CRoCCo,使用高度可扩展的AMR库AMReX来支持块结构的自适应网格细化,并添加了对全曲线求解器的支持。我们还将CRoCCo中的计算内核移植到gpu上,以便在现代百亿亿级系统上进行扩展。我们介绍了克服性能挑战的技术,并在Summit系统上评估了更新后的代码CRoCCo v2.0,演示了比仅使用cpu的版本提高6倍到44倍的速度。
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Porting a Computational Fluid Dynamics Code with AMR to Large-scale GPU Platforms
Accurate modeling of turbulent hypersonic flows has tremendous scientific and commercial value, and applies to atmospheric flight, supersonic combustion, materials discovery and climate prediction. In this paper, we describe our experiences in extending the capabilities of and modernizing CRoCCo, an MPI-based, CPU-only compressible computational fluid dynamics code. We extend CRoCCo to support block-structured adaptive mesh refinement using a highly-scalable AMR library, AMReX, and add support for a fully curvilinear solver. We also port the computational kernels in CRoCCo to GPUs to enable scaling on modern exascale systems. We present our techniques for overcoming performance challenges and evaluate the updated code, CRoCCo v2.0, on the Summit system, demonstrating a 6× to 44× speedup over the CPU-only version.
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