• DocumentCode
    3513330
  • Title

    Visualization of Large Graphs Using GPU Computing

  • Author

    Jeowicz, Toma ; Kudelka, Milos ; Plato, Jan ; Snael, Vaclav

  • Author_Institution
    Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    662
  • Lastpage
    667
  • Abstract
    Graphs may be used to visualize relationships between objects. Relations are represented by edges and objects are called nodes. When graph is drawn, one can easily see and understand the basic structure of data. Many different applications can be found in social network analysis, computer networks, scientific literature analysis, etc. However drawing large graphs (thousands or a millions of nodes), is still challenging problem. There exist many different algorithms for drawing graphs. Each algorithm has specific behavior and different applications and limits. Some algorithms are focused on quality while others are more suitable for large graphs. This paper aims to speed up the computation using GPU, so larger graphs can be visualized in acceptable time, or visualization can be done even in real-time.
  • Keywords
    data visualisation; graphics processing units; GPU computing; graph edge; graph node; graph visualization; graphics processing unit; Algorithm design and analysis; Data visualization; Graphics processing units; Instruction sets; Kernel; Layout; Random access memory; Fruchterman-Reingold; GPU computing; fast graph visualization; large graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems (INCoS), 2013 5th International Conference on
  • Conference_Location
    Xi´an
  • Type

    conf

  • DOI
    10.1109/INCoS.2013.126
  • Filename
    6630509