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 2218 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 (Schenk@nlpkkt240) has 27,993,600 vertices and 366,327,376 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.

ACUSIM/Pres_Poisson	Alemdar/Alemdar	AMD/G2_circuit	AMD/G3_circuit	Andrews/Andrews
Andrianov/ex3sta1	Andrianov/fxm3_6	Andrianov/fxm4_6	Andrianov/ins2	Andrianov/lp1
Andrianov/lpl1	Andrianov/mip1	Andrianov/net100	Andrianov/net125	Andrianov/net150
Andrianov/net25	Andrianov/net4-1	Andrianov/net50	Andrianov/net75	Andrianov/pattern1