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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GHS_indef/cvxqp3	GHS_indef/darcy003	GHS_indef/dawson5	GHS_indef/dixmaanl	GHS_indef/d_pretok
GHS_indef/dtoc	GHS_indef/exdata_1	GHS_indef/helm2d03	GHS_indef/helm3d01	GHS_indef/k1_san
GHS_indef/laser	GHS_indef/linverse	GHS_indef/mario001	GHS_indef/mario002	GHS_indef/ncvxbqp1
GHS_indef/ncvxqp1	GHS_indef/ncvxqp3	GHS_indef/ncvxqp5	GHS_indef/ncvxqp7	GHS_indef/ncvxqp9