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/olesnik0	GHS_indef/qpband	GHS_indef/sit100	GHS_indef/sparsine	GHS_indef/spmsrtls
GHS_indef/stokes128	GHS_indef/stokes64	GHS_indef/stokes64s	GHS_indef/tuma1	GHS_indef/tuma2
GHS_indef/turon_m	GHS_psdef/apache1	GHS_psdef/apache2	GHS_psdef/audikw_1	GHS_psdef/bmw7st_1
GHS_psdef/bmwcra_1	GHS_psdef/copter1	GHS_psdef/copter2	GHS_psdef/crankseg_1	GHS_psdef/crankseg_2