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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GHS_psdef/vanbody	GHS_psdef/wathen100	GHS_psdef/wathen120	Gleich/flickr	Gleich/minnesota
Gleich/usroads	Gleich/usroads-48	Gleich/wb-cs-stanford	Gleich/wb-edu	Gleich/wikipedia-20051105
Gleich/wikipedia-20060925	Gleich/wikipedia-20061104	Gleich/wikipedia-20070206	Goodwin/goodwin	Goodwin/rim
Graham/graham1	Grund/b1_ss	Grund/b2_ss	Grund/bayer01	Grund/bayer02