Interactive parallel visualization of large particle datasets

  • Authors:
  • Kevin Liang;Patricia Monger;Huge Couchman

  • Affiliations:
  • McMaster University, Hamilton, ON;McMaster University, Hamilton, ON;Department of Physics and Astronomy, McMaster University, Hamilton, ON

  • Venue:
  • EG PGV'04 Proceedings of the 5th Eurographics conference on Parallel Graphics and Visualization
  • Year:
  • 2004

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Abstract

This paper presents a new interactive parallel method for direct visualization of large particle datasets. Based on a parallel rendering cluster, a frame rate of 9 frames-per-second is achieved for 2563 particles using 7 render nodes and a display node. This provides real time interaction and interactive exploration of large datasets, which has been a challenge for scientific visualization and other real time data mining applications. The system allows scientists to study and to analyze the simulation results by viewing the particle cube from different perspectives, flying through the simulation field, or diving into the internal structure of the particles. A dynamic data distribution technique is designed for visualizing a highlighted subset of the particle volume. It maintains the load balance of the system and minimize the network traffic by updating the rendering pipeline through reconfiguration of the rendering chain. The method can be easily extended to other large datasets such as hydrodynamic turbulence, fluid dynamics, and so on.