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Gantt charts are frequently used to explore execution traces of large-scaleparallel programs found in high-performance computing (HPC). In thesevisualizations, each parallel processor is assigned a row showing thecomputation state of a processor at a particular time. Lines are drawn betweenrows to show communication between these processors. When drawn to alignequivalent calls across rows, structures can emerge reflecting communicationpatterns employed by the executing code. However, though these structures havethe same definition at any scale, they are obscured by the density of renderedlines when displaying more than a few hundred processors. A more scalablemetaphor is necessary to aid HPC experts in understanding communication inlarge-scale traces. To address this issue, we first conduct an exploratorystudy to identify what visual features are critical for determining similaritybetween structures shown at different scales. Based on these findings, wedesign a set of glyphs for displaying these structures in dense charts. We thenconduct a pre-registered user study evaluating how well people interpretcommunication using our new representation versus their base depictions inlarge-scale Gantt charts. Through our evaluation, we find that ourrepresentation enables users to more accurately identify communication patternscompared to full renderings of dense charts. We discuss the results of ourevaluation and findings regarding the design of metaphors for extensiblestructures.

Design and Evaluation of Scalable Representations of Communication in Gantt Charts for Large-scale Execution Traces