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An Image-Based Approach to Extreme Scale in Situ Visualization and Analysis

机译:基于图像的极端尺度原位可视化和分析方法

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Extreme scale scientific simulations are leading a charge to exascale computation, and data analytics runs the risk of being a bottleneck to scientific discovery. Due to power and I/O constraints, we expect in situ visualization and analysis will be a critical component of these workflows. Options for extreme scale data analysis are often presented as a stark contrast: write large files to disk for interactive, exploratory analysis, or perform in situ analysis to save detailed data about phenomena that a scientists knows about in advance. We present a novel framework for a third option - a highly interactive, image-based approach that promotes exploration of simulation results, and is easily accessed through extensions to widely used open source tools. This in situ approach supports interactive exploration of a wide range of results, while still significantly reducing data movement and storage.
机译:极端规模的科学模拟正在引领百亿美元级计算的发展,而数据分析则冒着成为科学发现瓶颈的风险。由于电源和I / O的限制,我们希望原位可视化和分析将成为这些工作流程的关键组成部分。极端数据分析的选项通常以鲜明的对比出现:将大文件写到磁盘上进行交互式,探索性分析,或执行原位分析以保存有关科学家事先知道的现象的详细数据。我们为第三个选择提供了一个新颖的框架-一种高度交互的,基于图像的方法,可以促进对仿真结果的探索,并且可以通过广泛使用的开放源代码工具的扩展轻松访问。这种原位方法支持交互式探索各种结果,同时仍显着减少了数据移动和存储。

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