TeGViz.
Distributed Tera-scale Graph Generation and Visualization.

- I. OVERVIEW
- II. CODE
- III. PAPER
- IV. PERFORMANCE
- V. EXAMPLES OF TEGVIZ RESULTS
- VI. PEOPLE

How can we generate and visualize tera-scale graphs efficiently?
Graph generation and visualization are used in graph mining research with various applications including
simulation, sampling/extrapoloation, and graph understanding.

We proposes TegViz, a distributed Tera-scale graph generation and visualization software. It consists of two modules:

(1) The graph generation module Teg generates a wide range of graphs including Erdos-R'enyi random graph and realistic graphs including R-MAT and Kronecker directly on distributed systems.

(2) The visualization module Net-Ray summarizes graphs using spy plot, distribution plot, and correlation plot to find regularities and anomalies effectively and makes it easy to understand generated graphs.

> Fast generation using distributed systems

> Visualization of Tera-scale graph

We proposes TegViz, a distributed Tera-scale graph generation and visualization software. It consists of two modules:

(1) The graph generation module Teg generates a wide range of graphs including Erdos-R'enyi random graph and realistic graphs including R-MAT and Kronecker directly on distributed systems.

(2) The visualization module Net-Ray summarizes graphs using spy plot, distribution plot, and correlation plot to find regularities and anomalies effectively and makes it easy to understand generated graphs.

TeGViz provides:

> Tera-scale graph generation > Fast generation using distributed systems

> Visualization of Tera-scale graph

We implemented TeGViz on top of Hadoop.

Currently, TeGViz supports:

- Random graph generator

- R-MAT graph generator

- Kronecker graph generator

- Visualization of Tera-scale graph with spy plot, distribution plot, and correlation plot

The binary of TeGViz is available. You can download it here.

Currently, TeGViz supports:

- Random graph generator

- R-MAT graph generator

- Kronecker graph generator

- Visualization of Tera-scale graph with spy plot, distribution plot, and correlation plot

The binary of TeGViz is available. You can download it here.

ByungSoo Jeon, Inah jeon, U Kang

15th IEEE International Conference on Data Mining (ICDM) 2015, Atlantic City, USA.

[PDF] [BIBTEX]

The following figure shows the performance of our propsosed graph generator,TeG.

Comparison of the running time between TeG and existing graph generators.
The label 'O.O.M.' means 'Out Of Memory'. In R-MAT and random graph, existing generators run out of memory when the numbers of edges are beyond 10^6 and 10^7 each, respectively, while TeG continues to run. Also, our Kronecker graph generator runs beyond 10^7.
Note that TeG generates up to 16384x larger graphs than existing generators.

ByungSoo Jeon (Department of Computer Science and Engineering, Seoul National University)

U Kang (Department of Computer Science and Engineering, Seoul National University)

Copyright © 2015, By Data Mining Laboratory, Department of Computer Science and Engineering, Seoul National University, All Rights Reserved.

Last Update: Oct 26, 2015