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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Priebel/162bit	Priebel/176bit	Priebel/192bit	Priebel/208bit	Puri/ABACUS_shell_hd
Puri/ABACUS_shell_ld	Puri/ABACUS_shell_md	Puri/ABACUS_shell_ud	Qaplib/lp_nug05	Qaplib/lp_nug06
Qaplib/lp_nug07	Qaplib/lp_nug08	Qaplib/lp_nug12	Qaplib/lp_nug15	Qaplib/lp_nug20
Qaplib/lp_nug30	QCD/conf5_0-4x4-10	QCD/conf5_0-4x4-14	QCD/conf5_0-4x4-18	QCD/conf5_0-4x4-22