A gallery of large graphs

graph drawing of matrices in 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. The resulting gallery contains the drawing of graphs as represented by 2272 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 graph (Schenk@nlpkkt240) has 27,993,600 vertices and 366,327,376 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_64	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