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.

FEMLAB/sme3Db	FEMLAB/sme3Dc	FEMLAB/waveguide3D	FIDAP/ex1	FIDAP/ex10
FIDAP/ex10hs	FIDAP/ex11	FIDAP/ex12	FIDAP/ex13	FIDAP/ex14
FIDAP/ex15	FIDAP/ex18	FIDAP/ex19	FIDAP/ex2	FIDAP/ex20
FIDAP/ex21	FIDAP/ex22	FIDAP/ex23	FIDAP/ex24	FIDAP/ex25