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.

 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