A gallery of large graphs

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 1890 sparse matrices in this collection. Each of these sparse matrices (for rectangular matrix, an augmented matrix is formed first) 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 has 8863287 vertices and 44185251 edges. A simple coloring scheme is used: if the matrix has real entries, coloring is based on the entry value, otherwise it is based on the edge length.

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	Sandia/fpga_dcop_08	Sandia/fpga_dcop_09	Sandia/fpga_dcop_10
Sandia/fpga_dcop_11	Sandia/fpga_dcop_12	Sandia/fpga_dcop_13	Sandia/fpga_dcop_14	Sandia/fpga_dcop_15
Sandia/fpga_dcop_16	Sandia/fpga_dcop_17	Sandia/fpga_dcop_18	Sandia/fpga_dcop_19	Sandia/fpga_dcop_20