As visualization is applied to larger data sets residing in more diverse hardware environments, visualization frameworks need to adapt. Rendering techniques are currently a major limiter since they tend to be built around central processing with all of the geometric data present. This is not a fundamental requirement of information visualization. This paper presents Abstract Rendering (AR), a technique for eliminating the centralization requirement while preserving some forms of interactivity. AR is based on the observation that pixels are fundamentally bins, and that rendering is essentially a binning process on a lattice of bins. By providing a more flexible binning process, the majority of rendering can be done with the geometric information stored out-of-core. Only the bin representations need to reside in memory. This approach enables: (1) rendering on large datasets without requiring large amounts of working memory, (2) novel and useful control over image composition, (3) a direct means of distributing the rendering task across processes, and (4) high-performance interaction techniques on large datasets. This paper introduces AR in a theoretical context, provides an overview of an implementation, and discusses how it has been applied to large-scale data visualization problems.

Date Published: 3 February 2014
PDF: 13 pages
Proc. SPIE 9017, Visualization and Data Analysis 2014, 90170K (3 February 2014); doi: 10.1117/12.2041200

Published in SPIE Proceedings Vol. 9017:
Visualization and Data Analysis 2014
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen, Editor(s)