Gantt charts are frequently used to explore execution traces of large-scale parallel programs found in high-performance computing (HPC). In these visualizations, each parallel processor is assigned a row showing the computation state of a processor at a particular time. Lines are drawn between rows to show communication between these processors. When drawn to align equivalent calls across rows, structures can emerge reflecting communication patterns employed by the executing code. However, though these structures have the same definition at any scale, they are obscured by the density of rendered lines when displaying more than a few hundred processors. A more scalable metaphor is necessary to aid HPC experts in understanding communication in large-scale traces. To address this issue, we first conduct an exploratory study to identify what visual features are critical for determining similarity between structures shown at different scales. Based on these findings, we design a set of glyphs for displaying these structures in dense charts. We then conduct a pre-registered user study evaluating how well people interpret communication using our new representation versus their base depictions in large-scale Gantt charts. Through our evaluation, we find that our representation enables users to more accurately identify communication patterns compared to full renderings of dense charts. We discuss the results of our evaluation and findings regarding the design of metaphors for extensible structures.
翻译:甘特图通常用于探索在高性能计算(HPC)中发现的大型平行程序(HPC)执行痕迹。在这些可视化中,每个平行处理器被指派一行,以显示某个特定时间处理器的计算状态。行之间绘制线以显示这些处理器之间的通信。在绘制对等的电话时,结构可以反映执行代码所使用的通信模式。虽然这些结构在任何规模上都有相同的定义,但它们被显示数百个处理器(HPC)所显示的线条密度所掩盖。在这些可视化处理器中,有必要用更可扩缩的比喻来帮助HPC专家了解大规模跟踪的通信状况。为了解决这一问题,我们首先进行一项探索性研究,以确定哪些视觉特征对于确定不同比例显示的结构之间的相似性至关重要。根据这些结果,我们设计了一系列用于在密集的图表中显示这些结构的拼图。我们随后进行了一项预先登记的用户研究,评估人们使用我们的新表达方式与在大型甘特图中的基本描述方式是如何解释通信的。我们通过评估发现,我们的代表能够更精确地展示我们的准确的图像。