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.

LPnetlib/lp_dfl001	LPnetlib/lp_e226	LPnetlib/lp_etamacro	LPnetlib/lp_fffff800	LPnetlib/lp_finnis
LPnetlib/lp_fit1d	LPnetlib/lp_fit1p	LPnetlib/lp_fit2d	LPnetlib/lp_fit2p	LPnetlib/lp_ganges
LPnetlib/lp_gfrd_pnc	LPnetlib/lp_greenbea	LPnetlib/lp_greenbeb	LPnetlib/lp_grow15	LPnetlib/lp_grow22
LPnetlib/lp_grow7	LPnetlib/lpi_bgdbg1	LPnetlib/lpi_bgetam	LPnetlib/lpi_bgindy	LPnetlib/lpi_bgprtr