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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Chen@pkustk02

Chen/pkustk02
Chen@pkustk03

Chen/pkustk03
Chen@pkustk04

Chen/pkustk04
Chen@pkustk05

Chen/pkustk05
Chen@pkustk06

Chen/pkustk06
Chen@pkustk07

Chen/pkustk07
Chen@pkustk08

Chen/pkustk08
Chen@pkustk09

Chen/pkustk09
Chen@pkustk10

Chen/pkustk10
Chen@pkustk11

Chen/pkustk11
Chen@pkustk12

Chen/pkustk12
Chen@pkustk13

Chen/pkustk13
Chen@pkustk14

Chen/pkustk14
Chevron@Chevron1

Chevron/Chevron1
Chevron@Chevron2

Chevron/Chevron2
Chevron@Chevron3

Chevron/Chevron3
Chevron@Chevron4

Chevron/Chevron4
Clark@tomographic1

Clark/tomographic1
Cote@mplate

Cote/mplate
Cote@vibrobox

Cote/vibrobox

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