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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HB@bp_1200

HB/bp_1200
HB@bp_1400

HB/bp_1400
HB@bp_1600

HB/bp_1600
HB@bp_200

HB/bp_200
HB@bp_400

HB/bp_400
HB@bp_600

HB/bp_600
HB@bp_800

HB/bp_800
HB@can_1054

HB/can_1054
HB@can_1072

HB/can_1072
HB@can_144

HB/can_144
HB@can_161

HB/can_161
HB@can_187

HB/can_187
HB@can_229

HB/can_229
HB@can_24

HB/can_24
HB@can_256

HB/can_256
HB@can_268

HB/can_268
HB@can_292

HB/can_292
HB@can_445

HB/can_445
HB@can_61

HB/can_61
HB@can_62

HB/can_62

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