Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Large Model Visualization : Techniques and Applications

The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture.The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture

Doctor of Philosophy

dissertationDataflow pipeline models are widely used in visualization systems. Despite recent advancements in parallel architecture, most systems still support only a single CPU or a small collection of CPUs such as a SMP workstation. Even for systems that are specifically tuned towards parallel visualization, their execution models only provide support for data-parallelism while ignoring taskparallelism and pipeline-parallelism. With the recent popularization of machines equipped with multicore CPUs and multi-GPU units, these visualization systems are undoubtedly falling further behind in reaching maximum efficiency. On the other hand, there exist several libraries that can schedule program executions on multiple CPUs and/or multiple GPUs. However, due to differences in executing a task graph and a pipeline along with their APIs being considerably low-level, it still remains a challenge to integrate these run-time libraries into current visualization systems. Thus, there is a need for a redesigned dataflow architecture to fully support and exploit the power of highly parallel machines in large-scale visualization. The new design must be able to schedule executions on heterogeneous platforms while at the same time supporting arbitrarily large datasets through the use of streaming data structures. The primary goal of this dissertation work is to develop a parallel dataflow architecture for streaming large-scale visualizations. The framework includes supports for platforms ranging from multicore processors to clusters consisting of thousands CPUs and GPUs. We achieve this in our system by introducing the notion of Virtual Processing Elements and Task-Oriented Modules along with a highly customizable scheduler that controls the assignment of tasks to elements dynamically. This creates an intuitive way to maintain multiple CPU/GPU kernels yet still provide coherency and synchronization across module executions. We have implemented these techniques into HyperFlow which is made of an API with all basic dataflow constructs described in the dissertation, and a distributed run-time library that can be used to deploy those pipelines on multicore, multi-GPU and cluster-based platforms

Parallel interactive ray tracing and exploiting spatial coherence

Dissertação de mestrado em Engenharia de InformáticaRay tracing is a rendering technique that allows simulating a wide range of light transport phenomena, resulting on highly realistic computer generated imaging. Ray tracing is, however, computationally very demanding, compared to other techniques such as rasterization that achieves shorter rendering times by greatly simplifying the physics of light propagation, at the cost of less realistic images. The complexity of the ray tracing algorithm makes it unusable for interactive applications on machines without dedicated hardware, such as GPUs. The extreme task independent nature of the algorithm offers great potential for parallel processing, increasing the available computational power by using additional resources. This thesis studies different approaches and enhancements on the decomposition of workload and load balancing in a distributed shared memory cluster in order to achieve interactive frame rates. This thesis also studies approaches to enhance the ray tracing algorithm, by reducing the computational demand without decreasing the quality of the results. To achieve this goal, optimizations that depend on the rays’ processing order were implemented. An alternative to the traditional image plan traversal order, scan line, is studied, using space-filling curves. Results have shown linear speed-ups of the used ray tracer in a distributed shared memory cluster. They have also shown that spatial coherence can be used to increase the performance of the ray tracing algorithm and that the improvement depends of the traversal order of the image plane.O ray tracing é uma técnica de síntese de imagens que permite simular um vasto conjunto de fenómenos da luz, resultando em imagens geradas por computador altamente realistas. O ray tracing é, no entanto, computacionalmente muito exigente quando comparado com outras técnicas tais como a rasterização, a qual consegue tempos de síntese mais baixos mas com imagens menos realistas. A complexidade do algoritmo de ray tracing torna o seu uso impossível para aplicações interativas em máquinas que não disponham de hardware dedicado a esse tipo de processamento, como os GPUs. No entanto, a natureza extremamente paralela do algoritmo oferece um grande potencial para o processamento paralelo. Nesta tese são analisadas diferentes abordagens e optimizações da decomposição das tarefas e balanceamento da carga num cluster de memória distribuída, por forma a alcançar frame rates interativas. Esta tese também estuda abordagens que melhoram o algoritmo de ray tracing, ao reduzir o esforço computacional sem perder qualidade nos resultados. Para esse efeito, foram implementadas optimizações que dependem da ordem pela qual os raios são processados. Foi estudada, nomeadamente, uma travessia do plano da imagem alternativa à tradicional, scan line, usando curvas de preenchimento espacial. Os resultados obtidos mostraram aumento de desempenho linear do ray tracer utilizado num cluster de memória distribuída. Demonstraram também que a coerência espacial pode ser usada para melhorar o desempenho do algoritmo de ray tracing e que estas melhorias dependem do algoritmo de travessia utilizado

Rectangular Selection of Components in Large 3D Models on the Web

We introduce a novel method for rectangular selection of components in large 3D models on the web. Our technique provides an easy to use solution that is developed for renderers with partial fragment shader support such as embedded systems running WebGL. This method was implemented using the Unity 3D game engine within the 3D Repo open source framework running on a web browser. A case study with industrial 3D models of varying complexity and object count shows that such a solution performs within reasonable rendering expectations even on underpowered devices without a dedicated graphics card

Real-time simulation and visualization of deformations on heightfields

Ankara : The Department of Computer Engineering and The Institute of Engineering and Science of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 117-121.The applications of computer graphics raise new expectations, such as realistic rendering, real-time dynamic scenes and physically correct simulations. The aim of this thesis is to investigate these problems on the height eld structure, an extended 2D model that can be processed e ciently by data-parallel architectures. This thesis presents methods for simulation of deformations on height eld as caused by triangular objects, physical simulation of objects interacting with height eld and advanced visualization of deformations. The height eld is stored in two di erent resolutions to support fast rendering and precise physical simulations as required. The methods are implemented as part of a large-scale height- eld management system, which applies additional level of detail and culling optimizations for the proposed methods and data structures. The solutions provide real-time interaction and recent graphics hardware (GPU) capabilities are utilized to achieve real-time results. All the methods described in this thesis are demonstrated by a sample application and performance characteristics and results are presented to support the conclusions.Yalçın, M AdilM.S

Visibility-Based Optimizations for Image Synthesis

Katedra počítačové grafiky a interakce