A Gallery of Large Graphs

graph visualization of matrices from the University of Florida Collection

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 using sfdp algorithm . The resulting gallery contains the drawing of graphs as represented by 2568 sparse matrices in this collection. Each of these sparse matrices (a rectangular matrix is treated as a bipartite graph) 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 graphs have tens of millions of nodes and over a billion of edges. A simple coloring scheme is used: longer edges are colored with colder colors, and short ones warmer. The graphs are in alphabetical order. Use the "Search" link to find graphs of specific characters.

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DRIVCAV/cavity03	DRIVCAV/cavity04	DRIVCAV/cavity05	DRIVCAV/cavity06	DRIVCAV/cavity07
DRIVCAV/cavity08	DRIVCAV/cavity09	DRIVCAV/cavity10	DRIVCAV/cavity11	DRIVCAV/cavity12
DRIVCAV/cavity13	DRIVCAV/cavity14	DRIVCAV/cavity15	DRIVCAV/cavity16	DRIVCAV/cavity17
DRIVCAV/cavity18	DRIVCAV/cavity19	DRIVCAV/cavity20	DRIVCAV/cavity21	DRIVCAV/cavity22