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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JGD_BIBD/bibd_16_8 |
JGD_BIBD/bibd_17_3 |
JGD_BIBD/bibd_17_4 |
JGD_BIBD/bibd_17_4b |
JGD_BIBD/bibd_17_8 |
JGD_BIBD/bibd_18_9 |
JGD_BIBD/bibd_19_9 |
JGD_BIBD/bibd_20_10 |
JGD_BIBD/bibd_22_8 |
JGD_BIBD/bibd_49_3 |
JGD_BIBD/bibd_81_2 |
JGD_BIBD/bibd_81_3 |
JGD_BIBD/bibd_9_3 |
JGD_BIBD/bibd_9_5 |
JGD_CAG/CAG_mat1916 |
JGD_CAG/CAG_mat364 |
JGD_CAG/CAG_mat72 |
JGD_Forest/TF10 |
JGD_Forest/TF11 |
JGD_Forest/TF12 |
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