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/adder_dcop_65	Sandia/adder_dcop_66	Sandia/adder_dcop_67	Sandia/adder_dcop_68	Sandia/adder_dcop_69
Sandia/adder_trans_01	Sandia/adder_trans_02	Sandia/ASIC_100k	Sandia/ASIC_100ks	Sandia/ASIC_320k
Sandia/ASIC_320ks	Sandia/ASIC_680k	Sandia/ASIC_680ks	Sandia/fpga_dcop_01	Sandia/fpga_dcop_02
Sandia/fpga_dcop_03	Sandia/fpga_dcop_04	Sandia/fpga_dcop_05	Sandia/fpga_dcop_06	Sandia/fpga_dcop_07