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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Bai@rbsb480

Bai/rbsb480
Bai@rdb1250

Bai/rdb1250
Bai@rdb1250l

Bai/rdb1250l
Bai@rdb200

Bai/rdb200
Bai@rdb200l

Bai/rdb200l
Bai@rdb2048

Bai/rdb2048
Bai@rdb2048_noL

Bai/rdb2048_noL
Bai@rdb3200l

Bai/rdb3200l
Bai@rdb450

Bai/rdb450
Bai@rdb450l

Bai/rdb450l
Bai@rdb5000

Bai/rdb5000
Bai@rdb800l

Bai/rdb800l
Bai@rdb968

Bai/rdb968
Bai@rw136

Bai/rw136
Bai@rw496

Bai/rw496
Bai@rw5151

Bai/rw5151
Bai@tols1090

Bai/tols1090
Bai@tols2000

Bai/tols2000
Bai@tols340

Bai/tols340
Bai@tols4000

Bai/tols4000

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