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Performancemodeling of a geophysics application to accelerate over-decomposition parameter tuning through simulation

机译:通过仿真加速过度分解参数调整的地球物理应用的性能

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Finite-difference methods are commonplace in High Performance Computing applications. Despite their apparent regularity, they often exhibit load imbalance that damages their efficiency. We characterize the spatial and temporal load imbalance ofOndes3D, a typical finite-differences application dedicated to earthquake modeling. Our analysis reveals imbalance originating from the structure of the input data, and from low-level CPU optimizations. Ondes3D was successfully ported to AMPI/CHARM++ using over-decomposition and MPI process migration techniques to dynamically rebalance the load. However, this approach requires careful selection of the over-decomposition level, the load balancing algorithm, and its activation frequency. These choices are usually tied to application structure and platform characteristics. In this article, we propose a workflow that leverages the capabilities of SimGrid to conduct such study at low experimental cost. We rely on a combination of emulation, simulation, and application modeling that requires minimal codemodification and manages to capture both spatial and temporal load imbalance to faithfully predict the performance of dynamic load balancing.We evaluate the quality of our simulation by comparing simulation results with the outcome of real executions and demonstrate how this approach can be used to quickly find the optimal load balancing configuration for a given application/hardware configuration.
机译:有限差分方法在高性能计算应用中是常见的。尽管他们明显的规律性,但他们往往展示了损害其效率的负荷不平衡。我们的特征在于ofOndes3d的空间和时间负荷不平衡,是专用于地震建模的典型有限差异应用。我们的分析揭示了源自输入数据结构的不平衡,以及低级别CPU优化。 ondes3d使用过分解和MPI进程迁移技术成功移植到AMPI / Charm ++,以动态重新平衡负载。然而,这种方法需要仔细选择过分解级别,负载平衡算法及其激活频率。这些选择通常与应用结构和平台特征相关联。在本文中,我们提出了一种工作流程,利用SimGrid的能力以低实验成本进行此类研究。我们依赖于仿真,仿真和应用建模的组合,这需要最小的代码处理和管理来捕获空间和时间负载不平衡,以忠实地预测动态负载平衡的性能。我们通过将模拟结果与模​​拟结果进行比较来评估模拟的质量实际执行的结果,并演示如何使用这种方法来快速查找给定应用/硬件配置的最佳负载平衡配置。

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