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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LPnetlib@lp_degen3

LPnetlib/lp_degen3
LPnetlib@lp_dfl001

LPnetlib/lp_dfl001
LPnetlib@lp_e226

LPnetlib/lp_e226
LPnetlib@lp_etamacro

LPnetlib/lp_etamacro
LPnetlib@lp_fffff800

LPnetlib/lp_fffff800
LPnetlib@lp_finnis

LPnetlib/lp_finnis
LPnetlib@lp_fit1d

LPnetlib/lp_fit1d
LPnetlib@lp_fit1p

LPnetlib/lp_fit1p
LPnetlib@lp_fit2d

LPnetlib/lp_fit2d
LPnetlib@lp_fit2p

LPnetlib/lp_fit2p
LPnetlib@lp_ganges

LPnetlib/lp_ganges
LPnetlib@lp_gfrd_pnc

LPnetlib/lp_gfrd_pnc
LPnetlib@lp_greenbea

LPnetlib/lp_greenbea
LPnetlib@lp_greenbeb

LPnetlib/lp_greenbeb
LPnetlib@lp_grow15

LPnetlib/lp_grow15
LPnetlib@lp_grow22

LPnetlib/lp_grow22
LPnetlib@lp_grow7

LPnetlib/lp_grow7
LPnetlib@lpi_bgdbg1

LPnetlib/lpi_bgdbg1
LPnetlib@lpi_bgetam

LPnetlib/lpi_bgetam
LPnetlib@lpi_bgindy

LPnetlib/lpi_bgindy

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