Visualizing the Five-dimensional Torus Network of the IBM Blue Gene/Q
Visualizing the Five-dimensional Torus Network of the IBM Blue Gene/Q
复制标题
可视化 IBM Blue Gene/Q 的五维环面网络
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
B. Hamann
中科院分区：
文献类型：
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作者：
Collin M. McCarthy;Katherine E. Isaacs;A. Bhatele;P. Bremer;B. Hamann
了解并行应用程序和通过其交换数据的互连网络之间的交互对于优化现代超级计算机的性能至关重要。然而，最近的超级计算体系结构使用的网络没有自然的低维表示，这使得它们很难理解或可视化。特别是，高维环面网络很常见，在排名前十的超级计算机中有四台使用，在Graph500榜单上排名前十的计算机中有八台使用。提出了一种新的五维环面网络可视化方法。我们使用四个连接的视图以不同的细节级别描述网络，使分析人员能够观察一般的大规模流量模式，同时查看网络任何特定部分中的单个链路或离群值。我们通过对运行在IBM Blue Gene/Q体系结构上的pF3D模拟的网络流量进行分析来演示该方法，并展示了该方法对于理解和优化并行应用行为是如何直观和有效的。
Understanding the interactions between a parallel application and the interconnection network over which it exchanges data is critical to optimizing performance in modern supercomputers. However, recent supercomputing architectures use networks that do not have natural low-dimensional representations, making them difficult to comprehend or visualize. In particular, high-dimensional torus networks are common and are used in four of the top ten supercomputers and eight of the top ten on the Graph500 list. We present a new visualization of five-dimensional torus networks. We use four connected views depicting the network at different levels of detail, allowing analysts to observe general large-scale traffic patterns while simultaneously viewing individual links or outliers in any specific section of the network. We demonstrate this approach by analyzing network traffic for a pF3D simulation running on the IBM Blue Gene/Q architecture, and show how it is both intuitive and effective for understanding and optimizing parallel application behavior.