Visualization of dynamic processes in scientific high-performance computing is an immensely data intensive endeavor. Application codes have recently demonstrated scaling to full-size Exascale machines, and generating high-quality data for visualization is consequently on the machine-scale, easily spanning 100s of TBytes of input to generate a single video frame. In situ visualization, the technique to consume the many-node decomposed data in-memory, as exposed by applications, is the dominant workflow. Although in situ visualization has achieved tremendous progress in the last decade, scaling to system-size together with the application codes that produce its data, there is one important question that we cannot skip: is what we produce insightful and inspiring?

翻译：科学高性能计算中动态过程的可视化是一项数据密集型任务。应用程序代码近期已展现出可扩展至全尺寸百亿亿级机器的能力，因此生成高质量可视化数据也随之达到机器级规模——单帧视频的输入数据轻松超过数百TB。即时可视化技术通过内存直接消耗应用暴露的多节点分解数据，已成为主流工作流。尽管过去十年间即时可视化取得了显著进展，能够与生成数据的应用程序代码同步扩展至系统级规模，但有一个核心问题我们无法回避：我们产出的内容是否具有洞察力且能激发灵感？