Visual analysis of large and complex data often requires multiple analysts with diverse expertise and different perspectives to collaborate in order to reveal hidden structures and gain insight in the data. While collaborative visualization allows multiple users to collectively work on the same analytic task, the user side computing devices can be used to share the computation workload for demanding data transformations and visualization calculations. In this paper, we present a heterogeneous computing framework for effective utilization of all the connected client devices to enhance the usability of online visualization applications.

Presenter(s)

Jianping Li , University of California, Davis

Jia-Kai Chou , University of California, Davis

Kwan-Liu Ma , University of California, Davis