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_28	Sandia/fpga_dcop_29	Sandia/fpga_dcop_30	Sandia/fpga_dcop_31	Sandia/fpga_dcop_32
Sandia/fpga_dcop_33	Sandia/fpga_dcop_34	Sandia/fpga_dcop_35	Sandia/fpga_dcop_36	Sandia/fpga_dcop_37
Sandia/fpga_dcop_38	Sandia/fpga_dcop_39	Sandia/fpga_dcop_40	Sandia/fpga_dcop_41	Sandia/fpga_dcop_42
Sandia/fpga_dcop_43	Sandia/fpga_dcop_44	Sandia/fpga_dcop_45	Sandia/fpga_dcop_46	Sandia/fpga_dcop_47