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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HB/gre_1107	HB/gre_115	HB/gre_185	HB/gre_216a	HB/gre_216b
HB/gre_343	HB/gre_512	HB/hor_131	HB/ibm32	HB/illc1033
HB/illc1850	HB/impcol_a	HB/impcol_b	HB/impcol_c	HB/impcol_d
HB/impcol_e	HB/jagmesh1	HB/jagmesh2	HB/jagmesh3	HB/jagmesh4