Abstract
Graphs provide a powerful way to model complex structures such as chemical compounds, proteins, images, and program dependence. The previous practice for experiments in graph indexing techniques is that the author of a newly proposed technique does not implement existing indexes on his own code base, but instead uses the original authors' binary executables and reports only the wall clock time. However, we observed that this practice may result in several problems [6]. In order to address these problems, we have implemented all representative graph indexing techniques on a common framework called iGraph [6]. In this demonstration we showcase iGraph and its visual tools using several real datasets and their workloads. For selected queries of the workloads, we show several unique features including visual performance analysis.
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