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.

Andrianov/pf2177	ATandT/onetone1	ATandT/onetone2	ATandT/pre2	ATandT/twotone
Averous/epb0	Averous/epb1	Averous/epb2	Averous/epb3	Bai/af23560
Bai/bfwa398	Bai/bfwa62	Bai/bfwa782	Bai/bfwb398	Bai/bfwb62
Bai/bfwb782	Bai/bwm200	Bai/bwm2000	Bai/cdde1	Bai/cdde2