论文标题
基于平行的SFC的网格分区和负载平衡
Parallel SFC-based mesh partitioning and load balancing
论文作者
论文摘要
现代超级计算机允许以提高精度模拟复杂现象。最终，这需要更精细的几何离散化，并具有更多的网格元素。在这种情况下，并推断到Exascale范式上，网格划分的操作，例如发电，适应或分区，成为模拟工作流程中的关键瓶颈。在本文中，我们专注于网格分区。特别是，我们提出了基于希尔伯特空间填充曲线的内部平行网格分区者进行的一些改进。 此外，利用其性能，我们介绍了基于SFC的分区用于动态负载平衡的应用。该方法基于对运行时不平衡的直接监视以及网格的随后重新分配。考虑到以前的迭代中的所有测量值，使用最小二乘近似值评估了优化分区的目标权重。这样，最终分区就对应于所参与计算设备的平均性能。
Modern supercomputers allow the simulation of complex phenomena with increased accuracy. Eventually, this requires finer geometric discretizations with larger numbers of mesh elements. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, adaptation or partition, become a critical bottleneck within the simulation workflow. In this paper, we focus on mesh partitioning. In particular, we present some improvements carried out on an in-house parallel mesh partitioner based on the Hilbert Space-Filling Curve. Additionally, taking advantage of its performance, we present the application of the SFC-based partitioning for dynamic load balancing. This method is based on the direct monitoring of the imbalance at runtime and the subsequent re-partitioning of the mesh. The target weights for the optimized partitions are evaluated using a least-squares approximation considering all measurements from previous iterations. In this way, the final partition corresponds to the average performance of the computing devices engaged.
