Abstract
Visualization is an effective way of identifying the patterns of interests (such as communities) in graphs including social networks and Web [8,6]. There have been a number of tools developed for graph visualizations, e.g., Tulip, Gephi and GMine [8]. All of these tools use the CPU as the main power to calculate the graph layouts for visualization, such as force-directed layout [2]. However, the layout calculation is usually computation intensive, for example, the force-directed layout has the complexity of O(N 3), where N is the number of vertexes in the graph. In our experiments, the CPU-based solution takes more than half one hours on the CPU to layout a graph with 14.5 thousand vertexes.
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Zhong, J., He, B. (2011). GViewer: GPU-Accelerated Graph Visualization and Mining. In: Datta, A., Shulman, S., Zheng, B., Lin, SD., Sun, A., Lim, EP. (eds) Social Informatics. SocInfo 2011. Lecture Notes in Computer Science, vol 6984. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24704-0_35
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DOI: https://doi.org/10.1007/978-3-642-24704-0_35
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