Parallel graphics and visualization

Computer Graphics and Visualization are two fields that continue to evolve at a fast pace, always addressing new application areas and achieving better and faster results. The volume of data processed by such applications keeps getting larger and the illumination and light transport models used to generate pictorial representations of this data keep getting more sophisticated. Richer illumination and light transport models allow the generation of richer images that convey more information about the phenomenons or virtual worlds represented by the data and are more realistic and engaging to the user. The combination of large data sets, rich illumination models and large, sophisticated displays results in huge workloads that cannot be processed sequentially and still maintain acceptable response times. Parallel processing is thus an obvious approach to such problems, creating the field of Parallel Graphics and Visualization. The Eurographics Symposium on Parallel Graphics and Visualization (EGPGV) gathers together researchers from all over the world to foster research focused on theoretical and applied issues critical to parallel and distributed computing and its application to all aspects of computer graphics, virtual reality, scientific and engineering visualization. This special issue is a collection of five papers selected from those presented at the 7th EGPGV, which took place in Lugano, Switzerland, in May, 2007. The research presented in this symposium has evolved over the years, often reflecting the evolution of the underlying systems’ architectures. While papers presented in the first few events focused on Single Instruction Multiple Data and Massively Parallel Multi-Processing systems, in recent years the focus was mainly on Symmetric Multiprocessing machines and PC clusters, often also including the utilization of multiple Graphics Processing Units. The 2007 event witnessed the first papers addressing multicore processors, thus following the general trend of computer systems’ architecture. The paper by Wald, Ize and Parker discusses acceleration structures for interactive ray tracing of dynamic scenes. They propose the utilization of Bounding Volume Hierarchies (BVH), which for deformable scenes can be rapidly updated by adjusting the bounding primitives while maintaining the hierarchy. To avoid a significant performance penalty due to a large mismatch between the scene geometry and the tree topology the BVH is rebuilt asynchronously and concurrently with rendering. According to the authors, in the near future interactive ray tracers are expected to run on highly parallel multicore architectures. Thus, all results reported were obtained on an 8 processor dual core system, totalling 16 cores. Gribble, Brownlee and Parker propose two algorithms targeting highly parallel multicore architectures enabling interactive navigation and exploration of large particle data sets with global illumination effects. Rendering samples are lazily evaluated using Monte Carlo path tracing, while visualization occurs asynchronously by using Dynamic Luminance Textures that cache the renderer results. The combined utilization of particle based simulation methods and global illumination enables the effective communication of subtle changes in the three-dimensional structure of the data. All results were also obtained on a 16 cores architecture. The paper by Thomaszweski, Pabst and Blochinger analyzes parallel techniques for physically based simulation, in particular, the time integration and collision handling phases. The former is addressed using the conjugate gradient algorithm and static problem decomposition, while the latter exhibits a dynamic structure, thus requiring fully dynamic task decomposition. Their results were obtained using three different quad-core systems. Hong and Shen derive an efficient parallel algorithm for symmetry computation in volume data represented by regular grids. Sequential detection of symmetric features in volumetric data sets has a prohibitive cost, thus requiring efficient parallel algorithms and powerful parallel systems. The authors obtained the reported results on a PC cluster with Infiniband and 64 nodes, each being a dual processor, single core Opteron. Bettio, Gobbetti, Marton and Pintore describe a scalable multiresolution rendering system targeting massive triangle meshes and driving different sized light field displays. The larger light field display ð1:6 0:9m2Þ is based on a special arrangement of projectors and a holographic screen. It allows multiple freely moving viewers to see the scene from their respective points of view and enjoy continuous horizontal parallax without any specialized viewing devices. To drive this 35 Mbeams display they use a scalable parallel renderer, resorting to out of core and level of detail techniques, and running on a 15 nodes PC cluster

Parallel graphics and visualization

Computer graphics and visualization are very active fields of Computer Science, continuously producing new and exciting results. However, the demand for increasingly faster feedback together with the huge volume of data usually associated with these applications, result on growing computational requirements. An efficient utilization of a multiplicity of computational and visualization resources expedites data processing for image generation, thus enabling such requirements to be met. This special issue of Parallel Computing attends to a selection of six papers out of 21 published at the past 2006 Eurographics Symposium on Parallel Graphics and Visualization, which was held in May 2006 in Braga, Portugal. The Eurographics Symposium on Parallel Graphics and Visualization focuses on theoretical and applied research issues critical to parallel and distributed computing and its application to all aspects of computer graphics, virtual reality, scientific and engineering visualization. Parallel graphics and visualization has evolved dramatically in the last few years. While previous works focused on SIMD architectures and standard PC clusters, more recent research moved to large displays and visualization oriented cluster architectures, which include graphics processing units at each node. This trend can be observed on the papers selected for this special issue: two papers present results on realistic rendering on PC clusters, two papers focus on parallel volume rendering resorting to graphics processing units and two papers address large displays and visualization clusters. The paper by Chalmers et al. combines parallel processing on a cluster with visual perception to achieve high fidelity physically based selective rendering at close to interactive rates. Thomaszewski et al. also use a PC cluster to perform physically based simulations of cloth, modelling both the material properties and the interaction with the surrounding scene. Bernardon et al. exploit CPU and GPU parallelism to render volumes of unstructured grids with time varying data. Other volume rendering technique is presented by Müller et al. using a sort last approach to perform volume ray casting on the fragment shaders of a GPU cluster. Cotting et al. present a software genlock approach for Windows, compatible with off-the-shelf graphics hardware, which can be employed to build cost effective VR installations such as large tiled displays. Lorenz and Brunnett add a new functionality to Chromium, where a new point-to-multipoint connection based on UDP allows rendering of large scenes synchronously on an arbitrary number of tiled displays at nearby constant performance. We hope that this special issue provides an interesting overview into parallel graphics and visualization. Further interest in the topic can be satisfied by following the Symposia on Parallel Graphics and Visualization, the 2007 one taking place in Lugano, Switzerland

Image Space Advection on graphics hardware

www.icg.tu-graz.ac.at The scientific visualization and computer graphics communities have witnessed a tremendous rise in graphics processing unit (GPU) related literature and methodology recently. This is due in part to the rapidly increasing processing speed offered by graphics cards. Parallel to this, we have seen several advances made in the area of texture-based flow visualization. We present a texture-based flow visualization technique, Image Space Advection (ISA), that takes advantage of the computing power offered by recent, state-of-theart GPUs. We have implemented a completely GPU-based version of the ISA algorithm. Here we describe our implementation in detail, including both the advantages and disadvantages of implementing ISA on the GPU. The result is state-of-the-art technique that demonstrates the latest in terms of both flow visualization methodology and GPU programming

Parallel methods for isosurface visualization

Journal Articleisosurface extraction and vis utilization is crucial for explorative scientific visualization of extremely large scientific data. The shear number of polygons extracted and the subsequent rendering time limit interactivity. We explore two solutions to this problem: exploiting parallel graphics hardware and parallel isosurface extraction/rendering via ray-tracing

"gtrellis": an R/Bioconductor package for making genome-level Trellis graphics

BACKGROUND: Trellis graphics are a visualization method that splits data by one or more categorical variables and displays subsets of the data in a grid of panels. Trellis graphics are broadly used in genomic data analysis to compare statistics over different categories in parallel and reveal multivariate relationships. However, current software packages to produce Trellis graphics have not been designed with genomic data in mind and lack some functionality that is required for effective visualization of genomic data. RESULTS: Here we introduce the gtrellis package which provides an efficient and extensible way to visualize genomic data in a Trellis layout. gtrellis provides highly flexible Trellis layouts which allow efficient arrangement of genomic categories on the plot. It supports multiple-track visualization, which makes it straightforward to visualize several properties of genomic data in parallel to explain complex relationships. In addition, gtrellis provides an extensible framework that allows adding user-defined graphics. CONCLUSIONS: The gtrellis package provides an easy and effective way to visualize genomic data and reveal high dimensional relationships on a genome-wide scale. gtrellis can be flexibly extended and thus can also serve as a base package for highly specific purposes. gtrellis makes it easy to produce novel visualizations, which can lead to the discovery of previously unrecognized patterns in genomic data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1051-4) contains supplementary material, which is available to authorized users

Research in computer science

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32

Visualization and Tracking of Parallel CFD Simulations

We describe a system for interactive visualization and tracking of a 3-D unsteady computational fluid dynamics (CFD) simulation on a parallel computer. CM/AVS, a distributed, parallel implementation of a visualization environment (AVS) runs on the CM-5 parallel supercomputer. A CFD solver is run as a CM/AVS module on the CM-5. Data communication between the solver, other parallel visualization modules, and a graphics workstation, which is running AVS, are handled by CM/AVS. Partitioning of the visualization task, between CM-5 and the workstation, can be done interactively in the visual programming environment provided by AVS. Flow solver parameters can also be altered by programmable interactive widgets. This system partially removes the requirement of storing large solution files at frequent time steps, a characteristic of the traditional 'simulate (yields) store (yields) visualize' post-processing approach

Research in computer science

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system

Scout: a hardware-accelerated system for quantitatively driven visualization and analysis

Journal ArticleQuantitative techniques for visualization are critical to the successful analysis of both acquired and simulated scientific data. Many visualization techniques rely on indirect mappings, such as transfer functions, to produce the final imagery. In many situations, it is preferable and more powerful to express these mappings as mathematical expressions, or queries, that can then be directly applied to the data. In this paper, we present a hardware-accelerated system that provides such capabilities and exploits current graphics hardware for portions of the computational tasks that would otherwise be executed on the CPU. In our approach, the direct programming of the graphics processor using a concise data parallel language, gives scientists the capability to efficiently explore and visualize data sets

Research on Visualization of Multi-Dimensional Real-Time Traffic Data Stream Based on Cloud Computing

AbstractBased on efficient continuous parallel query series algorithm supporting multi-objective optimization, by using visual graphics technology for traffic data streams for efficient real-time graphical visualization, it improve human-computer interaction, to realize real-time and visual data analysis and to improve efficiency and accuracy of the analysis. This paper employs data mining processing and statistical analysis on real-time traffic data stream, based on the parameters standards of various data mining algorithms, and by using computer graphics and image processing technology, converts graphics or images and make them displayed on the screen according to the system requirements, in order to track, forecast and maintain the operating condition of all traffic service systems effectively