Solving nearest neighbors problem on GPU to speed up the Fruchterman-Reingold graph layout algorithm

2015 ◽  
Author(s):  
Vojtech Uher ◽  
Petr Gajdos ◽  
Tomas Jezowicz
Keyword(s):  
Nearest Neighbors ◽  
Graph Layout ◽  
Layout Algorithm ◽  
Speed Up

A similarity metric designed to speed up, using hardware, the recommender systems k-nearest neighbors algorithm

2013 ◽  
Vol 51 ◽  
pp. 27-34 ◽  
Author(s):  
Jesús Bobadilla ◽  
Fernando Ortega ◽  
Antonio Hernando ◽  
Guillermo Glez-de-Rivera
Keyword(s):  
Recommender Systems ◽  
Nearest Neighbors ◽  
K Nearest Neighbors ◽  
Similarity Metric ◽  
Speed Up

scholarly journals A graph layout algorithm for drawing metabolic pathways

2001 ◽  
Vol 17 (5) ◽  
pp. 461-467 ◽  
Author(s):  
M. Y. Becker ◽  
I. Rojas
Keyword(s):  
Metabolic Pathways ◽  
Graph Layout ◽  
Layout Algorithm

scholarly journals Force-Directed Graph Layouts by Edge Sampling

2019 ◽  
Author(s):  
Robert Gove
Keyword(s):  
Directed Graph ◽  
Graph Visualization ◽  
Graph Layout ◽  
Spring Force ◽  
Graph Layouts ◽  
Speed Up ◽  
Sampling Algorithms ◽  
Edge Sampling ◽  
Force Calculation ◽  
Comparable Quality

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/

A stable graph layout algorithm for processes

2019 ◽  
Vol 38 (3) ◽  
pp. 725-737
Author(s):  
Robin J.P. Mennens ◽  
Roeland Scheepens ◽  
Michel A. Westenberg
Keyword(s):  
Graph Layout ◽  
Layout Algorithm

scholarly journals ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e98679 ◽  
Author(s):  
Mathieu Jacomy ◽  
Tommaso Venturini ◽  
Sebastien Heymann ◽  
Mathieu Bastian
Keyword(s):  
Network Visualization ◽  
Graph Layout ◽  
Layout Algorithm

A New Constraint-Based Compound Graph Layout Algorithm for Drawing Biochemical Networks

2011 ◽  
pp. 407-424
Author(s):  
Sabri Skhiri dit Gabouje ◽  
Esteban Zimányi
Keyword(s):  
Genetic Regulation ◽  
Biochemical Networks ◽  
Visualization Tool ◽  
Graph Layout ◽  
Layout Algorithm ◽  
Data Semantics ◽  
Visualization Tools ◽  
Generic Representation ◽  
Compound Graph ◽  
Single Graph

Due to the huge amount of information available in biochemical databases, biologists need sophisticated tools to accurately extract the information from such databases and to interpret it correctly. Those tools must be able to dynamically generate any kind of biochemical subgraph (i.e., metabolic pathways, genetic regulation, signal transduction, etc.) in a single graph. The visualization tools must be able to cope with such graphs and to take into account the particular semantics of all kinds of biochemical subgraphs. Therefore, such tools need generic graph layout algorithms that adapt their behavior to the data semantics. In this paper we present the Constrained Compound Graph Layout (C2GL) algorithm designed for the generic representation of biochemical graphs and in which users can represent knowledge about how to draw graphs in accordance with the biochemical semantics. We show how we implemented the C2GL algorithm in the Visual BioMaze framework, the visualization tool of the BioMaze project.

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