Faster data structures and graphics hardware techniques for high performance rendering

Computer generated imagery is used in a wide range of disciplines, each with different requirements. As an example, real-time applications such as computer games have completely different restrictions and demands than offline rendering of feature films. A game has to render quickly using only limited resources, yet present visually adequate images. Film and visual effects rendering may not have strict time requirements but are still required to render efficiently utilizing huge render systems with hundreds or even thousands of CPU cores. In real-time rendering, with limited time and hardware resources, it is always important to produce as high rendering quality as possible given the constraints available. The first paper in this thesis presents an analytical hardware model together with a feed-back system that guarantees the highest level of image quality subject to a limited time budget. As graphics processing units grow more powerful, power consumption becomes a critical issue. Smaller handheld devices have only a limited source of energy, their battery, and both small devices and high-end hardware are required to minimize energy consumption not to overheat. The second paper presents experiments and analysis which consider power usage across a range of real-time rendering algorithms and shadow algorithms executed on high-end, integrated and handheld hardware. Computing accurate reflections and refractions effects has long been considered available only in offline rendering where time isn’t a constraint. The third paper presents a hybrid approach, utilizing the speed of real-time rendering algorithms and hardware with the quality of offline methods to render high quality reflections and refractions in real-time. The fourth and fifth paper present improvements in construction time and quality of Bounding Volume Hierarchies (BVH). Building BVHs faster reduces rendering time in offline rendering and brings ray tracing a step closer towards a feasible real-time approach. Bonsai, presented in the fourth paper, constructs BVHs on CPUs faster than contemporary competing algorithms and produces BVHs of a very high quality. Following Bonsai, the fifth paper presents an algorithm that refines BVH construction by allowing triangles to be split. Although splitting triangles increases construction time, it generally allows for higher quality BVHs. The fifth paper introduces a triangle splitting BVH construction approach that builds BVHs with quality on a par with an earlier high quality splitting algorithm. However, the method presented in paper five is several times faster in construction time

On-the-Fly Power-Aware Rendering

Power saving is a prevailing concern in desktop computers and, especially, in battery-powered devices such as mobile phones. This is generating a growing demand for power-aware graphics applications that can extend battery life, while preserving good quality. In this paper, we address this issue by presenting a real-time power-efficient rendering framework, able to dynamically select the rendering configuration with the best quality within a given power budget. Different from the current state of the art, our method does not require precomputation of the whole camera-view space, nor Pareto curves to explore the vast power-error space; as such, it can also handle dynamic scenes. Our algorithm is based on two key components: our novel power prediction model, and our runtime quality error estimation mechanism. These components allow us to search for the optimal rendering configuration at runtime, being transparent to the user. We demonstrate the performance of our framework on two different platforms: a desktop computer, and a mobile device. In both cases, we produce results close to the maximum quality, while achieving significant power savings

Scalable Real-Time Rendering for Extremely Complex 3D Environments Using Multiple GPUs

In 3D visualization, real-time rendering of high-quality meshes in complex 3D environments is still one of the major challenges in computer graphics. New data acquisition techniques like 3D modeling and scanning have drastically increased the requirement for more complex models and the demand for higher display resolutions in recent years. Most of the existing acceleration techniques using a single GPU for rendering suffer from the limited GPU memory budget, the time-consuming sequential executions, and the finite display resolution. Recently, people have started building commodity workstations with multiple GPUs and multiple displays. As a result, more GPU memory is available across a distributed cluster of GPUs, more computational power is provided throughout the combination of multiple GPUs, and a higher display resolution can be achieved by connecting each GPU to a display monitor (resulting in a tiled large display configuration). However, using a multi-GPU workstation may not always give the desired rendering performance due to the imbalanced rendering workloads among GPUs and overheads caused by inter-GPU communication. In this dissertation, I contribute a multi-GPU multi-display parallel rendering approach for complex 3D environments. The approach has the capability to support a high-performance and high-quality rendering of static and dynamic 3D environments. A novel parallel load balancing algorithm is developed based on a screen partitioning strategy to dynamically balance the number of vertices and triangles rendered by each GPU. The overhead of inter-GPU communication is minimized by transferring only a small amount of image pixels rather than chunks of 3D primitives with a novel frame exchanging algorithm. The state-of-the-art parallel mesh simplification and GPU out-of-core techniques are integrated into the multi-GPU multi-display system to accelerate the rendering process

B.O.G.G.L.E.S.: Boundary Optical GeoGraphic Lidar Environment System

The purpose of this paper is to describe a pseudo X-ray vision system that pairs a Lidar scanner with a visualization device. The system as a whole is referred to as B.O.G.G.L.E.S. There are several key factors that went into the development of this system and the background information and design approach are thoroughly described. B.O.G.G.L.E.S functionality is depicted through the use of design constraints and the analysis of test results. Additionally, many possible developments for B.O.G.G.L.E.S are proposed in the paper. This indicates that there are various avenues of improvement for this project that could be implemented in the future