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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MathWorks/Kuu	MathWorks/Muu	MathWorks/Pd	MathWorks/Pd_rhs	MathWorks/pivtol
MathWorks/QRpivot	MathWorks/Sieber	MathWorks/tomography	MathWorks/TS	MaxPlanck/shallow_water1
MaxPlanck/shallow_water2	McRae/ecology1	McRae/ecology2	Meszaros/aa01	Meszaros/aa03
Meszaros/aa3	Meszaros/aa4	Meszaros/aa5	Meszaros/aa6	Meszaros/air02