In-situ processing has widely been recognized as an effective approach for the visualization and analysis of large-scale simulation outputs from modern HPC systems. One of the most common approaches for batch-based in-situ visualization is the image- or video-based approach. In this kind of approach, a large number of rendered images are generated from different viewpoints at each time step and has proven useful for detailed analysis of the main simulation results. However, during test runs and model calibration runs before the main simulation run, a quick overview might be sufficient and useful. In this work, we focused on selecting the viewpoints which provide as much information as possible by using information entropy to maximize the subsequent visual analysis task. However, by simply following the selected viewpoints at each of the visualization time steps will probably lead to a rapidly changing video, which can impact the understanding. Therefore, we have also worked on an efficient camera path estimation approach for connecting selected viewpoints, at regular intervals, to generate a smooth video. This resulting video is expected to assist in rapid understanding of the underlying simulation phenomena and can be helpful to narrow down the temporal region of interest to minimize the turnaround time during detailed visual exploration via image- or video-based visual analysis of the main simulation run. We implemented and evaluated the proposed approach using the OpenFOAM CFD application, on an x86-based Server and an ARM A64FX-based supercomputer (Fugaku), and we obtained positive evaluations from domain scientists.

翻译：现场处理已被广泛认为是现代高性能计算系统大规模模拟输出的可视化与分析的有效方法。基于批次的可视化中，最常用的方式之一是图像或视频方法。该方法在每个时间步从不同视角生成大量渲染图像，已被证明有助于对主要模拟结果进行详细分析。然而，在主模拟运行前的测试运行和模型校准阶段，快速概览可能足以满足需求且更为实用。本研究聚焦于通过信息熵选择能提供尽可能多信息的视角，以最大化后续可视分析任务的效果。但若在每个可视化时间步简单跟随所选视角，可能导致视频画面快速切换，影响理解。因此，我们进一步研究了高效的摄像机路径估计方法，用于在固定时间间隔内连接选定视角，生成平滑视频。该视频有望辅助快速理解底层模拟现象，并有助于缩小感兴趣的时间区域，从而减少通过基于图像或视频的主模拟运行视觉分析进行详细探索时的周转时间。我们基于OpenFOAM计算流体力学应用，在x86服务器与ARM A64FX超算系统（Fugaku）上实现并评估了所提方法，获得了领域科学家的积极评价。