The task of real time rendering of today's volumetric datasets is still being tackled by several research groups. A quick calculation of the amount of computation required for real-time rendering of a high resolution volume puts us in the teraflop range. Yet, the demand to support such rendering capabilities is increasing due to emerging technologies such as virtual surgery simulation and rapid prototyping. There are five main approaches to overcoming this seemingly insurmountable performance barrier: (i) data reduction by means of model extraction or data simplification, (ii) realization of special-purpose volume rendering engines, (iii) software-based algorithm optimization and acceleration, (iv) implementation on general purpose parallel architectures, and (v) use of contemporary of-the-shelf graphics hardware. In this presentation we first describe the vision of real-time high-resolution volume rendering and estimate the computing power it demands. We survey the state-of-the art in...

During the last years serveral methods have been developed to visualize three dimensional volume data on multiprocessor computer systems. Most of these algorithms were strongly adapted to the underlying target architecture, and often did not take account of requirements such as scalability, portability, or memory minimization. The following paper outlines a new approach to rendering large scale volume data on distributed memory parallel computers. Within this framework, the only limiting factor concerning the resolution of the processed data is the node local memory. Furthermore, porting to other multiprocessor systems is straight forward, and scalability with increasing numbers of processors is achieved. Keywords and Phrases: volume rendering, massively parallel computer, MIMD 1 Introduction The visualization of three-dimensional volume data is one of the most time consuming and memory intensive techniques in computer graphics. Although there exist fast back-tofront projection meth...

this paper. D. Asimov reviewed the paper. This work was supported under NASA contract NAS2-12961.

The task of efficient rendering of today's volumetric datasets is still being tackled by several research groups around the world. A quick calculation of the amount of computation required for interactive rendering of a high resolution volume puts us in the teraflop range. Yet, the demand to support such rendering capabilities is increasing due to emerging technologies such as virtual surgery simulation and rapid prototyping. There are five main approaches to overcoming this seemingly insurmountable performance barrier: (i) data reduction by means of model extraction or data simplification, (ii) realization of special-purpose volume rendering engines, (iii) software-based algorithm optimization and acceleration, (iv) implementation on general purpose parallel architectures, and (v) use of contemporary of-the-shelf graphics hardware. In this presentation we first describe the vision of real-time high-resolution volume rendering and estimate the computing power it demands. W...

In this paper we focus on two aspects: (1)the application of grid technology to allow a group of geographically disperse users to accomplish a given task collaboratively; (2) distributed scientific visualization through grid. Henceforth, we firstly describe some collaborative environments. Then, visualization techniques that can be implemented in grids are focused. These techniques can be integrated in a collaborative visualization system through grid technology.

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