Interactive parallel visualization of large particle datasets

Authors:
Kevin Liang;Patricia Monger;Huge Couchman
Affiliations:
Research & HPC Support, McMaster University, Hamilton, ON, Canada L8S 4M1;Research & HPC Support, McMaster University, Hamilton, ON, Canada L8S 4M1;Department of Physics and Astronomy, McMaster University, Hamilton, ON, Canada L8S 4M1
Venue:
Parallel Computing - Parallel graphics and visualization
Year:
2005

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Abstract

This paper presents a new interactive parallel visualization method for large particle datasets by directly rendering individual particles based on a parallel rendering cluster. A frame rate of 9 frames-per-second is achieved for 256^3 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. A dynamic data distribution technique is designed for highlighting a subset of the particle volume. It maintains load balance of the system and minimizes network traffic by reconfiguring the rendering chain. Experiments show that on a given subset, interactive manipulation of the subset usually requires less than 3% of the particles inside the subset to be redistributed among all render nodes. The method can be easily extended to other large datasets such as hydrodynamic turbulence, fluid dynamics, and so on.