Dynamic Scalable Visualization for Collaborative Scientific Applications

  • Authors:
  • Kai Li;Matthew Hibbs;Grant Wallace;Olga Troyanskaya

  • Affiliations:
  • Princeton University, New Jersey;Princeton University, New Jersey;Princeton University, New Jersey;Princeton University, New Jersey

  • Venue:
  • IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
  • Year:
  • 2005

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Abstract

Science disciplines are experiencing a data avalanche. As a result, scientific research is limited by data analysis and visualization capabilities. We have been working closely with Genomic and Plasma Physics researchers on effective data visualization software tools. This paper reports our research on developing software tools for high-resolution display walls to alleviate the current limitation on visualization resolution and single-user window system. In the first case, we developed a novel data visualization tools for genomic data visualization that is dynamic and scale free. In the second case, we have developed a multi-cursor window system for shared data visualization for a collaborative environment. We have deployed both software tools to the scientific researchers. Our initial feedbacks show that these approaches have made significant impact on their productivity.