论文标题
通过代理应用程序建模前XASCALE AMR平行I/O工作负载
Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications
论文作者
论文摘要
本工作通过简单的代理应用程序研究了自适应网格细化（AMR）模拟的前外输入/输出（I/O）工作负载的建模。我们从峰顶超级计算机上运行的Amrex Castro框架中收集数据，以作为流体动力学SEDOV案例的各种尺度和网格分区，作为基线，以提供足够的覆盖面向公式的代理模型。非线性分析数据生产率是根据一组输入参数（例如输出频率，网格大小，级别数量以及Courant-Friedrichs-Lewy（CFL）条件编号，网格级别和仿真时间步骤的courant-friedrichs-Lewy（CFL）条件编号的量化的量化。然后将线性回归应用以制定一个简单的分析模型，该模型允许将AMREX输入转换为MACSIO代理I/O应用程序参数，从而在每个时间步骤中为数据生成提供一个简单的“内核”近似值。结果表明，MACSIO可以使用当前方法对峰顶超级计算机的一定程度的置信度模拟实际的AMREX非线性“静态” I/O工作负载。目的是通过轻巧的代理应用程序模型提供对AMR I/O工作负载的初始了解，以促进预期Exascale系统的自动点数据管理策略。
The present work investigates the modeling of pre-exascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple "kernel" approximation for data production at each time step. Results show that MACSio can simulate actual AMReX non-linear "static" I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.
