A Gallery of Large Graphs

graph visualization of matrices from the University of Florida Collection

Graph visualization is a way to discover and visualize structures in complex relations. What sort of structures are people who do large scale computation studying? We can get a glimpse by visualizing the thousands of sparse matrices submitted to the University of Florida Sparse Matrix collection using sfdp algorithm . The resulting gallery contains the drawing of graphs as represented by 2568 sparse matrices in this collection. Each of these sparse matrices (a rectangular matrix is treated as a bipartite graph) is viewed as the adjacency matrix of an undirected graph, and is laid out by a multilevel graph drawing algorithm. If the graph is disconnected, then the largest connected component is drawn. The largest graphs have tens of millions of nodes and over a billion of edges. A simple coloring scheme is used: longer edges are colored with colder colors, and short ones warmer. The graphs are in alphabetical order. Use the "Search" link to find graphs of specific characters.

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Sandia/fpga_dcop_08	Sandia/fpga_dcop_09	Sandia/fpga_dcop_10	Sandia/fpga_dcop_11	Sandia/fpga_dcop_12
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Sandia/fpga_dcop_18	Sandia/fpga_dcop_19	Sandia/fpga_dcop_20	Sandia/fpga_dcop_21	Sandia/fpga_dcop_22
Sandia/fpga_dcop_23	Sandia/fpga_dcop_24	Sandia/fpga_dcop_25	Sandia/fpga_dcop_26	Sandia/fpga_dcop_27