scholarly journals BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory

Author(s):  
Md. Khaledur Rahman ◽  
Majedul Haque Sujon ◽  
Ariful Azad
2013 ◽  
Vol 16 (3) ◽  
pp. 139-149 ◽  
Author(s):  
Wenqiang Dong ◽  
Xingyu Fu ◽  
Guangluan Xu ◽  
Yu Huang

2001 ◽  
Vol 17 (5) ◽  
pp. 461-467 ◽  
Author(s):  
M. Y. Becker ◽  
I. Rojas

NeuroImage ◽  
2011 ◽  
Vol 54 (3) ◽  
pp. 2176-2184 ◽  
Author(s):  
Alessandro Crippa ◽  
Leonardo Cerliani ◽  
Luca Nanetti ◽  
Jos B.T.M. Roerdink
Keyword(s):  

2016 ◽  
Vol 13 (2) ◽  
pp. 397-408 ◽  
Author(s):  
Yuji Fujita ◽  
Yoshi Fujiwara ◽  
Wataru Souma
Keyword(s):  

2019 ◽  
Author(s):  
Robert Gove

Recent work shows that sampling algorithms can be an effective tool for graph visualization. This paper extends prior work by applying edge sampling algorithms to speed up the spring force calculation in force-directed graph layout algorithms. An experiment on 72 graphs finds that some sampling algorithms achieve comparable quality as no sampling. This result is confirmed with visualizations of the graph layout results. However, runtime improvements are small, especially for graphs with 10,000 vertices or fewer, indicating that the runtime savings might not be worth the risk to layout quality. Therefore, this paper suggests that accurate spring forces may be more important to force-directed graph layout algorithms than accurate electric forces. A copy of this paper plus the code and data to reproduce the results are available at https://osf.io/4ja29/


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