AN INTERACTIVE REMOTE VISUALIZATION SYSTEM FOR MOBILE APPLICATION ACCESS

This paper introduces a remote visualization approach that enables the visualization of data sets on mobile devices or in web environments. With this approach the necessary computing power can be outsourced to a server environment. The developed system allows the rendering of 2D and 3D graphics on mobile phones or web browsers with high quality independent of the size of the original data set. Compared to known terminal server or other proprietary remote systems our approach offers a very simple way to integrate with a large variety of applications which makes it useful for real-life application scenarios in business processes

Cluster-based interactive volume rendering with Simian

technical reportCommodity-based computer clusters offer a cost-effective alternative to traditional largescale, tightly coupled computers as a means to provide high-performance computational and visualization services. The Center for the Simulation of Accidental Fires and Explosions (C-SAFE) at the University of Utah employs such a cluster, and we have begun to experiment with cluster-based visualization services. In particular, we seek to develop an interactive volume rendering tool for navigating and visualizing large-scale scientific datasets. Using Simian, an OpenGL volume renderer, we examine two approaches to cluster-based interactive volume rendering: (1) a ?cluster-aware? version of the application that makes explicit use of remote nodes through a message-passing interface, and (2) the unmodified application running atop the Chromium clustered rendering framework. This paper provides a detailed comparison of the two approaches by carefully considering the key issues that arise when parallelizing Simian. These issues include the richness of user interaction; the distribution of volumetric datasets and proxy geometry; and the degree of interactivity provided by the image rendering and compositing schemes. The results of each approach when visualizing two large-scale C-SAFE datasets are given, and we discuss the relative advantages and disadvantages that were considered when developing our cluster-based interactive volume rendering application

Doctor of Philosophy

dissertationRay tracing presents an efficient rendering algorithm for scientific visualization using common visualization tools and scales with increasingly large geometry counts while allowing for accurate physically-based visualization and analysis, which enables enhanced rendering and new visualization techniques. Interactivity is of great importance for data exploration and analysis in order to gain insight into large-scale data. Increasingly large data sizes are pushing the limits of brute-force rasterization algorithms present in the most widely-used visualization software. Interactive ray tracing presents an alternative rendering solution which scales well on multicore shared memory machines and multinode distributed systems while scaling with increasing geometry counts through logarithmic acceleration structure traversals. Ray tracing within existing tools also provides enhanced rendering options over current implementations, giving users additional insight from better depth cues while also enabling publication-quality rendering and new models of visualization such as replicating photographic visualization techniques