标题： 动态负载平衡技术用于颗粒流模拟 显示英文标题

标题： Dynamic Load Balancing Techniques for Particulate Flow Simulations

摘要： 并行多物理场仿真经常由于算法的耦合而出现负载不平衡，这些算法具有空间和时间变化的工作量。 因此，最小化这些不平衡是有益的，以减少求解时间并更好地利用可用的硬件资源。 以颗粒流为例，我们提出了并评估了处理这一挑战性任务的负载平衡技术。 这包括一个负载估计步骤，其中预测当前生成的工作量。 我们详细描述了如何开发这样的工作量估算器。 在第二步中，应用如空间填充曲线或图划分等负载分配策略，以动态地在可用进程中分配负载。 为了比较和分析它们的性能，我们将这些技术应用于基准场景，并观察到负载不平衡减少了近四倍。 这导致空间填充曲线的整体运行时间减少了14%。 显示英文摘要

摘要： Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is thus desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. Taking particulate flows as an illustrating example application, we present and evaluate load balancing techniques that tackle this challenging task. This involves a load estimation step in which the currently generated workload is predicted. We describe in detail how such a workload estimator can be developed. In a second step, load distribution strategies like space-filling curves or graph partitioning are applied to dynamically distribute the load among the available processes. To compare and analyze their performance, we employ these techniques to a benchmark scenario and observe a reduction of the load imbalances by almost a factor of four. This results in a decrease of the overall runtime by 14% for space-filling curves.