Simulating hand-drawn illustration can succinctly express information in a manner that is communicative and informative. We present a framework for an interactive direct stipple rendering of volume and surface-based objects. By combining the principles of artistic and scientific illustration, we explore several feature enhancement techniques to create effective, interactive visualizations of scientific and medical data sets. We also introduce a rendering mechanism that generates appropriate point lists at all resolutions during an automatic preprocess and modifies rendering styles through different combinations of these feature enhancements. The new system is an effective way to interactively preview large, complex volume and surface data sets in a concise, meaningful, and illustrative manner. Stippling is effective for many applications and provides a quick and efficient method to investigate both volume and surface models.

We have constructed a distributed parallel ray tracing system that interactively produces isosurface renderings from large data sets on a cluster of commodity PCs. The program was derived from the SCI Institute's interactive ray tracer (*-Ray), which utilizes small to large shared memory platforms, such as the SGI Origin series, to interact with very large-scale data sets. Making this approach work efficiently on a cluster requires attention to numerous system-level issues, especially when rendering data sets larger than the address space of each cluster node. The rendering engine is an image parallel ray tracer with a supervisor/workers organization. Each node in the cluster runs a multithreaded application. A minimal abstraction layer on top of TCP links the nodes, and enables asynchronous message handling. For large volumes, render threads obtain data bricks on demand from an object-based software distributed shared memory. Caching improves performance by reducing the amount of data transfers for a reasonable working set size. For large data sets, the cluster-based interactive ray tracer performs comparably with an SGI Origin system. We examine the parameter space of the renderer and provide experimental results for interactive rendering of large (7.5 GB) data sets.

A b s t r a c t Commodity-based computer clusters offer a cost-effective alternative to traditional large-scale, tightly coupled computers as a means to provide high-performance computational and visualization services. The Center for the Simulation of Accidental Fires and Ex­ plosions (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 applica­ tion 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 dis­ cuss the relative advantages and disadvantages that were considered when developing our cluster-based interactive volume rendering application. A bstra ct Commodity-based computer clusters offer a cost-effective alterna­ tive to traditional large-scale, tightly coupled computers as a means to provide high-performance computational and visualization ser­ vices. The Center for the Simulation of Accidental Fires and Explo­ sions (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 exam­ ine 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 …

This index covers all technical items - papers, correspondence, reviews, etc. that appeared in this periodical during 2003, and items from previous years that were commented upon or corrected in 2003. Departments and other items may be also covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author’s name. The primary entry includes the coauthors’ names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author’s name, the publication abbreviation, month, and year, and inclusive pages. Subject cross-references are included to assist in finding items of interest. Note that the item title is found only under the primary entry in the Author Index.

Pen and ink rendering techniques provide artistic, illustrative, and informative representations of objects. With recent advances in hardware graphics technology, several researchers have developed interactive non-photorealistic rendering techniques, including hatching, toon rendering, and silhouettes. However, the stippling method of drawing and shading using dots has not received as much focus. In this paper, we present an interactive system for stipple drawing of surface-based objects that provides illustrative stipple renderings of multiple objects and includes adaptation of the stippling to provide a consistent rendering of objects at any scale. We also describe the use of the latest graphics hardware capabilities for accelerating the rendering by performing the silhouette rendering on the GPU and the stipple density enhancement calculations as a vertex program.

This paper describes the implementation and performance evaluation of a parallel volume renderer capable of handling large volumetric data sets. We implement our volume renderer on a cluster of 32 Linux PC’s using OpenGL, MPI and a binary–swap compositing algorithm. We also give hints for achieving good performance when using OpenGL and MPI on a Linux visualization cluster.