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Coupling Exascale Multiphysics Applications: Methods and Lessons Learned

机译:耦合Exascale Multiphysics应用程序:学习方法和经验教训

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With the growing computational complexity of science and the complexity of new and emerging hardware, it is time to re-evaluate the traditional monolithic design of computational codes. One new paradigm is constructing larger scientific computational experiments from the coupling of multiple individual scientific applications, each targeting their own physics, characteristic lengths, and/or scales. We present a framework constructed by leveraging capabilities such as in-memory communications, workflow scheduling on HPC resources, and continuous performance monitoring. This code coupling capability is demonstrated by a fusion science scenario, where differences between the plasma at the edges and at the core of a device have different physical descriptions. This infrastructure not only enables the coupling of the physics components, but it also connects in situ or online analysis, compression, and visualization that accelerate the time between a run and the analysis of the science content Results from runs on Titan and Cori are presented as a demonstration.
机译:随着科学的越来越多的计算复杂性和新的和新兴硬件的复杂性,是时候重新评估传统的计算代码整体设计。一个新的范例是从多个单独的科学应用的耦合构建更大的科学计算实验,每个科学应用程序统治其自己的物理,特征长度和/或尺度。我们提出了一种通过利用内存通信,工作流程调度的能力构成的框架,以及连续性能监控。该码耦合能力由融合科学场景进行说明,其中边缘处等离子体和设备核心之间的等离子体之间的差异具有不同的物理描述。此基础架构不仅可以实现物理组件的耦合,而且还可以在原位或在线分析,压缩和可视化连接,以加速运行和科学内容分析之间的时间,从泰坦和Cori上运行呈现为演示。

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