Performance Analysis of a 3D Parallel Volume Rendering Application on Scalable Tiled Displays (original) (raw)

Image-Space-Parallel Direct Volume Rendering on a Cluster of PCs

Lecture Notes in Computer Science, 2003

An image-space-parallel, ray-casting-based direct volume rendering algorithm is developed for rendering of unstructured data grids on distributed-memory parallel architectures. For efficiency in screen workload calculations, a graph-partitioning-based tetrahedral cell clustering technique is used. The main contribution of the work is at the proposed model, which formulates the screen partitioning problem as a hypergraph partitioning problem. It is experimentally verified on a PC cluster that, compared to the previously suggested jagged partitioning approach, the proposed approach results in both better load balancing in local rendering and less communication overhead in data migration phases.

Giga-Scale Multiresolution Volume Rendering on Distributed Display Clusters

Lecture Notes in Computer Science, 2011

Visualizing the enormous level of detail comprised in many of today's data sets is a challenging task and demands special processing techniques as well as a presentation on appropriate display devices. Desktop computers and laptops are often not suited for this task because data sets are simply too large and the limited screen size of these devices prevents users from perceiving the entire data set and severely restricts collaboration. Large high-resolution displays that combine the images of multiple smaller devices to form one large display area have proven to be an adequate solution to the ever-growing quantity of available data.

High-Performance Scalable Graphics Architecture for High-Resolution Displays

2005

We present the Scalable Adaptive Graphics Environment (SAGE), a graphics streaming architecture for supporting collaborative scientific visualization environments with potentially hundreds of megapixels of contiguous display resolution. In collaborative scientific visualization it is crucial to share high resolution visualizations as well as high definition video among groups of collaborators at local or remote sites. Our network-centered architecture allows collaborators to simultaneously run multiple visualization applications on local or remote clusters and share the visualizations by streaming the pixels of each application over ultra high speed networks to large tiled displays. This streaming architecture is designed such that the output of arbitrary M by N pixel rendering cluster nodes can be streamed to X by Y pixel display screens allowing for userdefinable layouts on the display. This dynamic pixel routing capability of our architecture allows users to freely move and resize each application's imagery over the tiled displays in runtime, tightly synchronizing the multiple visualization streams to form a single stream. Experimental results show that our architecture can support visualization at multi-ten-megapixel resolution with reasonable frame rates using gigabit networks.

Functionality and Performance Visualization of the Distributed High Quality Volume Renderer (HVR)

2012

Volume rendering systems are designed to provide means to enable scientists and a variety of experts to interactively explore volume data through 3D views of the volume. However, volume rendering techniques are computationally intensive tasks. Moreover, parallel distributed volume rendering systems and multi-threading architectures were suggested as natural solutions to provide an acceptable volume rendering performance for very large volume data sizes, such as Electron Microscopy data (EM). This in turn adds another level of complexity when developing and manipulating volume rendering systems. Given that distributed parallel volume rendering systems are among the most complex systems to develop, trace and debug, it is obvious that traditional debugging tools do not provide enough support. As a consequence, there is a great demand to provide tools that are able to facilitate the manipulation of such systems. This can be achieved by utilizing the power of compute graphics in designin...

A Distributed Rendering System for Scientific Visualization

2002

Parallel, real-time rendering using clusters of commodity components has rapidly become a topic of significant interest within the scientific visualization community. This paper describes the design and implementation of a very large scale, distributed system that renders 6144 × 3072 pixel images and projects them across a 14 × 7 display wall at 35 frames per second.

Scalable rendering on PC clusters

IEEE Computer Graphics and Applications, 2001

This paper presents initial results from research targeted at the development of cost-effective scalable visualization and rendering technologies. The implementations of two 3D graphics libraries based on the popular sort-last and sort-first parallel rendering techniques are discussed. An important goal of these implementations is to provide scalable rendering capability for extremely large datasets (>> 5 million polygons). Applications can use these libraries for either run-time visualization, by linking to an existing parallel simulation, or for traditional postprocessing by linking to an interactive display program. The use of parallel, hardware-accelerated rendering on commodity hardware is leveraged to achieve high performance. Current performance results show that, using our current hardware (a small 16-node cluster), we can utilize up to 85% of the aggregate graphics performance and achieve rendering rates in excess of 20 million polygons/second using OpenGL® with lighting, Gouraud shading, and individually specified triangles (not t-stripped).

Scalable Graphics Architecture for High-Resolution Displays

We envision situation-rooms and research laboratories in which all the walls are made from seamless ultra-high-resolution displays fed by data streamed over ultra-high-speed networks from distantly located visualization, storage servers, and high definition video cameras . It will allow local and distributed groups of researchers to work together on large amounts of distributed heterogeneous datasets. We are taking the next steps toward this vision by building LambdaVision -an 11x5 tiled display with a total resolution of 100 megapixels and developing SAGE, the Scalable Adaptive Graphics Environment (see ). SAGE allows the seamless display of various networked applications over the high-resolution displays. Each visualization application (such as 3D rendering, remote desktop, video streams, very large 2D maps) streams its rendered pixels (or graphics primitives) to SAGE, allowing for any given layout onto the displays (e.g. the output of arbitrary M by N pixel rendering cluster nodes can be streamed to X by Y pixel display screens).

Estimation of Volume Rendering Efficiency with GPU in a Parallel Distributed Environment

Procedia Computer Science, 2013

Visualization methods of medical imagery based on volumetric data constitute a fundamental tool for medical diagnosis, training and pre-surgical planning. Often, large volume sizes and/or the complexity of the required computations present serious obstacles for reaching higher levels of realism and real-time performance. Performance and efficiency are two critical aspects in traditional algorithms based on complex lighting models. To overcome these problems, a volume rendering algorithm, PD-Render intra for individual networked nodes in a parallel distributed architecture with a single GPU per node is presented in this paper. The implemented algorithm is able to achieve photorealistic rendering as well as a high signal-tonoise ratio at interactive frame rates. Experiments show excellent results in terms of efficiency and performance for rendering medical volumes in real time.

Data distribution strategies for high-resolution displays

Computers & Graphics, 2001

Large-scale and high-resolution displays are increasingly being used for next-generation interactive 3D graphics applications, including large-scale data visualization, immersive virtual environments, and collaborative design. These systems must include a very high-performance and scalable 3D rendering subsystem in order to generate high-resolution images at real-time frame rates.

A survey of architectures for volume rendering

IEEE Engineering in Medicine and Biology Magazine, 1990

Titan, AT&T Pixel-Machine, Silicon Graphics 4 D , Hewlett Packard TurboSRX, SUN TAAC-1, Pixar, and the Pixel-Planes machine, are briefly reviewed in this article. Other software based systems [12,25,27,54,61,66] are outside the scope of this survey. The interested reader in the topic of volume visualization is referred to the reference list [32,63,64].