We introduce a GPU-accelerated simulation tool, named Modeling on Shallow Flows with Efficient Simulation for Two-Phase Debris Flows (MoSES_2PDF), of which the input and output data can be linked to the GIS system for engineering application. MoSES_2PDF is developed based on the CUDA structure so that it can well run with different NVIDIA GPU cards, once the CUDA vers. 9.2 (or higher) is installed. The performance of the MoSES_2PDF is evaluated, and it is found that the present GPU-CUDA implementation can enhance efficiency by up to 230 folds, depending on the PC/workstations, models of GPU card, and the mesh numbers in the computation domain. Two numerical examples are illustrated with two distinct initial inflow conditions, which are included in two modes of MoSES_2PDF, respectively. In the numerical example of a large-scale event, the 2009 Hsiaolin event, the results computed by two distinct NVIDIA GPU cards (RTX-2080-Ti and Tesla-V100) are found to be identical but only tiny deviation is figured out in comparison with the results computed by the conventional single-core CPU-code. It is speculated to be caused by the different structures in the source codes and some float/double operations. In addition to the illustration in the GIS system, the computed results by MoSES\_2PDF can also be shown with animated 3D graphics in the ANSI-Platform, where the user can interact with 3D scenes. The feasibility, features, and facilities of MoSES\_2PDF are demonstrated with respect to the two numerical examples concerning two real events.
翻译:我们引入了一个名为“光流模型”的GPU加速模拟工具,名为“浅流模型”,为两阶段碎片流高效模拟(MOSES_2PDF),其中输入和输出数据可以与工程应用的地理信息系统连接。MOSES_2PDF是根据CUDA结构开发的,因此一旦安装了CUDA vers. 9.2(或更高),它就可以使用不同的 NVIDIDA GPU卡运行运行。评估了MOSES_2PDF的性能,并发现目前的GPU-CUDA实施可以提高多达230个折叠数的效率,这取决于PC/工作站、GPU卡模型和计算域内的网格数字。有两个数字示例显示了两个不同的初始流入条件,分别包含在MESES_2PDF的两种模式中。在大型事件的数字实例中,2009年Siaoollin事件,由两个不同的 NVIDA GP卡(RTX-20-80-DDD)和Tesla-VDF 数字结构中显示的二个数字变量,由O-I-DFS 显示的数值结构显示,在两个数字结构中,在两个数字结构中显示的数值结构中,由CES-DFFS-ILUDFFS 和两个数字结构显示的结果是相同的数字结构显示。