(The Eurographics Association, 2025) Aguilar, Luis Miguel; Al-Tarawneh, Ragaad; Humayoun, Shah Rukh; Diehl, Alexandra; Kucher, Kostiantyn; Médoc, Nicolas
The growing volume and complexity of data from sources like social media, IoT systems, and security devices highlight the need for scalable, high-performance visualization tools. Traditional web technologies such as SVG and Canvas often struggle with large datasets, limiting interactivity. We present WebGraphViz, a WebGL-based graph visualization tool that leverages GPU parallelism to overcome these limitations. Performance evaluations across three interaction experiments in both high- and low-performance environments show that WebGraphViz significantly outperforms its SVG-based counterpart, enabling smooth exploration of large-scale graph data.