Today's scientific simulations generate exceptionally large volumes of data, challenging the capacities of available I/O bandwidth and storage space. This necessitates a substantial reduction in data volume, for which error-bounded lossy compression has emerged as a highly effective strategy. A crucial metric for assessing the efficacy of lossy compression is visualization. Despite extensive research on the impact of compression on visualization, there is a notable gap in the literature concerning the effects of compression on the visualization of Adaptive Mesh Refinement (AMR) data. AMR has proven to be a potent solution for addressing the rising computational intensity and the explosive growth in data volume that requires storage and transmission. However, the hierarchical and multi-resolution characteristics of AMR data introduce unique challenges to its visualization, and these challenges are further compounded when data compression comes into play. This article delves into the intricacies of how data compression influences and introduces novel challenges to the visualization of AMR data.

翻译：当今科学模拟生成的数据量极为庞大，对现有的I/O带宽和存储空间容量构成了挑战。这要求大幅削减数据量，而有界误差有损压缩已成为一种非常有效的策略。评估有损压缩效果的关键指标之一是可视化。尽管已有大量关于压缩对可视化影响的研究，但文献中关于压缩对自适应网格细化（AMR）数据可视化影响的研究仍存在显著空白。AMR已被证明是应对计算强度日益增加以及需要存储和传输的数据量爆炸性增长的有效解决方案。然而，AMR数据的层次化和多分辨率特性为可视化带来了独特的挑战，而当数据压缩介入时，这些挑战进一步加剧。本文深入探讨了数据压缩如何影响AMR数据的可视化并引入新的挑战。