适配国产多节点GPU的二维非结构高性能水动力模型

A high-performance 2D unstructured hydrodynamic model for domestic multi-node GPU clusters

  • 摘要: 为满足国产信创环境下洪水数值模拟的高性能运算要求,研发了适配国产多节点GPU集群的二维非结构高性能水动力模型。该模型基于二维有限体积法的Godunov型数值格式,依托可移植异构计算接口(HIP)框架,采用C++编程语言实现适配国产GPU的高性能加速计算,为进一步提升计算效率,采用METIS区域分解法和消息传递接口技术(MPI)实现跨节点多GPU的高效协同计算。通过经典矩形溃坝算例及TOCE河算例验证了新研发模型具有良好的数值精度、可靠的稳定性和正确的分区通信技术,将模型在江苏省横山水库进行了应用测试,结果表明:在“米”级分辨率、1500万网格规模下,使用16个节点64块GPU可将计算耗时从3.76 h缩短至15 min,实现大规模、高分辨率洪水模拟由单卡“小时级”到多节点“分钟级”的效率跨越。新研发模型可完全适配国产软硬件环境,具有广泛工程应用前景。

     

    Abstract: To meet the computational demands of numerical flood simulation under China’s information technology innovation initiative, this study proposes a high-performance two-dimensional unstructured hydrodynamic model designed for domestic multi-node GPU clusters. The model is based on a Godunov-type finite volume scheme and is implemented in C++ using the Heterogeneous-Compute Interface for Portability (HIP) framework, enabling efficient acceleration on domestic GPUs. METIS-based domain decomposition and the message passing interface (MPI) are adopted to support collaborative computation across multiple GPUs and computing nodes, thereby improving parallel computing efficiency. Numerical tests using the classical rectangular dam-break benchmark and the Toce River case demonstrate that the model achieves satisfactory accuracy, stable computation, and reliable inter-domain communication. Field application to Hengshan Reservoir in Jiangsu Province further shows that, for a meter-scale simulation containing 15 million mesh cells, the use of 64 GPUs across 16 nodes reduced the total runtime from 3.76 h to 15 min. This result indicates a substantial improvement in computational efficiency for large-scale, high-resolution flood simulation, reducing runtime from the hourly scale on a single GPU to the minute scale on a multi-node GPU cluster. With compatibility across domestic hardware and software environments, the proposed model has strong potential for engineering applications in high-resolution flood modeling.

     

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