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

Foundations and Methods for GPU based Image Synthesis

Effects such as global illumination, caustics, defocus and motion blur are an integral part of generating images that are perceived as realistic pictures and cannot be distinguished from photographs. In general, two different approaches exist to render images: ray tracing and rasterization. Ray tracing is a widely used technique for production quality rendering of images. The image quality and physical correctness are more important than the time needed for rendering. Generating these effects is a very compute and memory intensive process and can take minutes to hours for a single camera shot. Rasterization on the other hand is used to render images if real-time constraints have to be met (e.g. computer games). Often specialized algorithms are used to approximate these complex effects to achieve plausible results while sacrificing image quality for performance. This thesis is split into two parts. In the first part we look at algorithms and load-balancing schemes for general purpose computing on graphics processing units (GPUs). Most of the ray tracing related algorithms (e.g. KD-tree construction or bidirectional path tracing) have unpredictable memory requirements. Dynamic memory allocation on GPUs suffers from global synchronization required to keep the state of current allocations. We present a method to reduce this overhead on massively parallel hardware architectures. In particular, we merge small parallel allocation requests from different threads that can occur while exploiting SIMD style parallelism. We speed-up the dynamic allocation using a set of constraints that can be applied to a large class of parallel algorithms. To achieve the image quality needed for feature films GPU-cluster are often used to cope with the amount of computation needed. We present a framework that employs a dynamic load balancing approach and applies fair scheduling to minimize the average execution time of spawned computational tasks. The load balancing capabilities are shown by handling irregular workloads: a bidirectional path tracer allowing renderings of complex effects at near interactive frame rates. In the second part of the thesis we try to reduce the image quality gap between production and real-time rendering. Therefore, an adaptive acceleration structure for screen-space ray tracing is presented that represents the scene geometry by planar approximations. The benefit is a fast method to skip empty space and compute exact intersection points based on the planar approximation. This technique allows simulating complex phenomena including depth-of-field rendering and ray traced reflections at real-time frame rates. To handle motion blur in combination with transparent objects we present a unified rendering approach that decouples space and time sampling. Thereby, we can achieve interactive frame rates by reusing fragments during the sampling step. The scene geometry that is potentially visible at any point in time for the duration of a frame is rendered in a rasterization step and stored in temporally varying fragments. We perform spatial sampling to determine all temporally varying fragments that intersect with a specific viewing ray at any point in time. Viewing rays can be sampled according to the lens uv-sampling to incorporate depth-of-field. In a final temporal sampling step, we evaluate the pre-determined viewing ray/fragment intersections for one or multiple points in time. This allows incorporating standard shading effects including and resulting in a physically plausible motion and defocus blur for transparent and opaque objects

Harnessing the power of GPUs for problems in real algebraic geometry

This thesis presents novel parallel algorithms to leverage the power of GPUs (Graphics Processing Units) for exact computations with polynomials having large integer coefficients. The significance of such computations, especially in real algebraic geometry, is hard to undermine. On massively-parallel architectures such as GPU, the degree of datalevel parallelism exposed by an algorithm is the main performance factor. We attain high efficiency through the use of structured matrix theory to assist the realization of relevant operations on polynomials on the graphics hardware. A detailed complexity analysis, assuming the PRAM model, also confirms that our approach achieves a substantially better parallel complexity in comparison to classical algorithms used for symbolic computations. Aside from the theoretical considerations, a large portion of this work is dedicated to the actual algorithm development and optimization techniques where we pay close attention to the specifics of the graphics hardware. As a byproduct of this work, we have developed high-throughput modular arithmetic which we expect to be useful for other GPU applications, in particular, open-key cryptography. We further discuss the algorithms for the solution of a system of polynomial equations, topology computation of algebraic curves and curve visualization which can profit to the full extent from the GPU acceleration. Extensive benchmarking on a real data demonstrates the superiority of our algorithms over several state-of-the-art approaches available to date. This thesis is written in English.Diese Arbeit beschäftigt sich mit neuen parallelen Algorithmen, die das Leistungspotenzial der Grafik-Prozessoren (GPUs) zur exakten Berechnungen mit ganzzahlige Polynomen nutzen. Solche symbolische Berechnungen sind von großer Bedeutung zur Lösung vieler Probleme aus der reellen algebraischen Geometrie. Für die effziente Implementierung eines Algorithmus auf massiv-parallelen Hardwarearchitekturen, wie z.B. GPU, ist vor allem auf eine hohe Datenparallelität zu achten. Unter Verwendung von Ergebnissen aus der strukturierten Matrix-Theorie konnten wir die entsprechenden Operationen mit Polynomen auf der Grafikkarte leicht übertragen. Außerdem zeigt eine Komplexitätanalyse im PRAM-Rechenmodell, dass die von uns entwickelten Verfahren eine deutlich bessere Komplexität aufweisen als dies für die klassischen Verfahren der Fall ist. Neben dem theoretischen Ergebnis liegt ein weiterer Schwerpunkt dieser Arbeit in der praktischen Implementierung der betrachteten Algorithmen, wobei wir auf der Besonderheiten der Grafikhardware achten. Im Rahmen dieser Arbeit haben wir hocheffiziente modulare Arithmetik entwickelt, von der wir erwarten, dass sie sich für andere GPU Anwendungen, insbesondere der Public-Key-Kryptographie, als nützlich erweisen wird. Darüber hinaus betrachten wir Algorithmen für die Lösung eines Systems von Polynomgleichungen, Topologie Berechnung der algebraischen Kurven und deren Visualisierung welche in vollem Umfang von der GPU-Leistung profitieren können. Zahlreiche Experimente belegen dass wir zur Zeit die beste Verfahren zur Verfügung stellen. Diese Dissertation ist in englischer Sprache verfasst

Parallel rendering algorithms for distributed-memory multicomputers

Ankara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1997.Thesis (Ph. D.) -- Bilkent University, 1997.Includes bibliographical references leaves 166-176.Kurç, Tahsin MertefePh.D

Ray Tracing Gems

This book is a must-have for anyone serious about rendering in real time. With the announcement of new ray tracing APIs and hardware to support them, developers can easily create real-time applications with ray tracing as a core component. As ray tracing on the GPU becomes faster, it will play a more central role in real-time rendering. Ray Tracing Gems provides key building blocks for developers of games, architectural applications, visualizations, and more. Experts in rendering share their knowledge by explaining everything from nitty-gritty techniques that will improve any ray tracer to mastery of the new capabilities of current and future hardware. What you'll learn: The latest ray tracing techniques for developing real-time applications in multiple domains Guidance, advice, and best practices for rendering applications with Microsoft DirectX Raytracing (DXR) How to implement high-performance graphics for interactive visualizations, games, simulations, and more Who this book is for: Developers who are looking to leverage the latest APIs and GPU technology for real-time rendering and ray tracing Students looking to learn about best practices in these areas Enthusiasts who want to understand and experiment with their new GPU

Polygon-based hidden surface elimination algorithms: serial and parallel

Chapter 1 introduces the need for rapid solutions of hidden surface elimination (HSE) problems in the interactive display of objects and scenes, as used in many application areas such as flight and driving simulators and CAD systems. It reviews the existing approaches to high-performance computer graphics and to parallel computing. It then introduces the central tenet of this thesis: that general purpose parallel computers may be usefully applied to the solution of HSE problems. Finally it introduces a set of metrics for describing sets of scene data, and applies them to the test scenes used in this thesis. Chapter 2 describes variants of several common image space hidden surface elimination algorithms, which solve the HSE problem for scenes described as collections of polygons. Implementations of these HSE algorithms on a traditional, serial, single microprocessor computer are introduced and theoretical estimates of their performance are derived. The algorithms are compared under identical conditions for various sets of test data. The results of this comparison are then placed in context with existing historical results. Chapter 3 examines the application of MIMD style parallelism to accelerate the solution of HSE problems. MIMD parallel implementations of the previously considered HSE algorithms are introduced. Their behaviour under various system configurations and for various data sets is investigated and compared with theoretical estimates. The theoretical estimates are found to match closely the experimental findings. Chapter 4 summarises the conclusions of this thesis, finding that HSE algorithms can be implemented to use an MIMD parallel computer effectively, and that of the HSE algorithms examined the z-buffer algorithm generally proves to be a good compromise solution

Efficient Many-Light Rendering of Scenes with Participating Media

We present several approaches based on virtual lights that aim at capturing the light transport without compromising quality, and while preserving the elegance and efficiency of many-light rendering. By reformulating the integration scheme, we obtain two numerically efficient techniques; one tailored specifically for interactive, high-quality lighting on surfaces, and one for handling scenes with participating media

Efficient rendering for three-dimensional displays

This thesis explores more efficient methods for visualizing point data sets on three-dimensional (3D) displays. Point data sets are used in many scientific applications, e.g. cosmological simulations. Visualizing these data sets in {3D} is desirable because it can more readily reveal structure and unknown phenomena. However, cutting-edge scientific point data sets are very large and producing/rendering even a single image is expensive. Furthermore, current literature suggests that the ideal number of views for 3D (multiview) displays can be in the hundreds, which compounds the costs. The accepted notion that many views are required for {3D} displays is challenged by carrying out a novel human factor trials study. The results suggest that humans are actually surprisingly insensitive to the number of viewpoints with regard to their task performance, when occlusion in the scene is not a dominant factor. Existing stereoscopic rendering algorithms can have high set-up costs which limits their use and none are tuned for uncorrelated {3D} point rendering. This thesis shows that it is possible to improve rendering speeds for a low number of views by perspective reprojection. The novelty in the approach described lies in delaying the reprojection and generation of the viewpoints until the fragment stage of the pipeline and streamlining the rendering pipeline for points only. Theoretical analysis suggests a fragment reprojection scheme will render at least 2.8 times faster than na\"{i}vely re-rendering the scene from multiple viewpoints. Building upon the fragment reprojection technique, further rendering performance is shown to be possible (at the cost of some rendering accuracy) by restricting the amount of reprojection required according to the stereoscopic resolution of the display. A significant benefit is that the scene depth can be mapped arbitrarily to the perceived depth range of the display at no extra cost than a single region mapping approach. Using an average case-study (rendering from a 500k points for a 9-view High Definition 3D display), theoretical analysis suggests that this new approach is capable of twice the performance gains than simply reprojecting every single fragment, and quantitative measures show the algorithm to be 5 times faster than a naïve rendering approach. Further detailed quantitative results, under varying scenarios, are provided and discussed

Real-time GPU-accelerated Out-of-Core Rendering and Light-field Display Visualization for Improved Massive Volume Understanding

Nowadays huge digital models are becoming increasingly available for a number of different applications ranging from CAD, industrial design to medicine and natural sciences. Particularly, in the field of medicine, data acquisition devices such as MRI or CT scanners routinely produce huge volumetric datasets. Currently, these datasets can easily reach dimensions of 1024^3 voxels and datasets larger than that are not uncommon. This thesis focuses on efficient methods for the interactive exploration of such large volumes using direct volume visualization techniques on commodity platforms. To reach this goal specialized multi-resolution structures and algorithms, which are able to directly render volumes of potentially unlimited size are introduced. The developed techniques are output sensitive and their rendering costs depend only on the complexity of the generated images and not on the complexity of the input datasets. The advanced characteristics of modern GPGPU architectures are exploited and combined with an out-of-core framework in order to provide a more flexible, scalable and efficient implementation of these algorithms and data structures on single GPUs and GPU clusters. To improve visual perception and understanding, the use of novel 3D display technology based on a light-field approach is introduced. This kind of device allows multiple naked-eye users to perceive virtual objects floating inside the display workspace, exploiting the stereo and horizontal parallax. A set of specialized and interactive illustrative techniques capable of providing different contextual information in different areas of the display, as well as an out-of-core CUDA based ray-casting engine with a number of improvements over current GPU volume ray-casters are both reported. The possibilities of the system are demonstrated by the multi-user interactive exploration of 64-GVoxel datasets on a 35-MPixel light-field display driven by a cluster of PCs. ------------------------------------------------------------------------------------------------------ Negli ultimi anni si sta verificando una proliferazione sempre più consistente di modelli digitali di notevoli dimensioni in campi applicativi che variano dal CAD e la progettazione industriale alla medicina e le scienze naturali. In modo particolare, nel settore della medicina, le apparecchiature di acquisizione dei dati come RM o TAC producono comunemente dei dataset volumetrici di grosse dimensioni. Questi dataset possono facilmente raggiungere taglie dell’ordine di 10243 voxels e dataset di dimensioni maggiori possono essere frequenti. Questa tesi si focalizza su metodi efficienti per l’esplorazione di tali grossi volumi utilizzando tecniche di visualizzazione diretta su piattaforme HW di diffusione di massa. Per raggiungere tale obiettivo si introducono strutture specializzate multi-risoluzione e algoritmi in grado di visualizzare volumi di dimensioni potenzialmente infinite. Le tecniche sviluppate sono “ouput sensitive” e la loro complessità di rendering dipende soltanto dalle dimensioni delle immagini generate e non dalle dimensioni dei dataset di input. Le caratteristiche avanzate delle architetture moderne GPGPU vengono inoltre sfruttate e combinate con un framework “out-of-core” in modo da offrire una implementazione di questi algoritmi e strutture dati più flessibile, scalabile ed efficiente su singole GPU o cluster di GPU. Per migliorare la percezione visiva e la comprensione dei dati, viene introdotto inoltre l’uso di tecnologie di display 3D di nuova generazione basate su un approccio di tipo light-field. Questi tipi di dispositivi consentono a diversi utenti di percepire ad occhio nudo oggetti che galleggiano all’interno dello spazio di lavoro del display, sfruttando lo stereo e la parallasse orizzontale. Si descrivono infine un insieme di tecniche illustrative interattive in grado di fornire diverse informazioni contestuali in diverse zone del display, così come un motore di “ray-casting out-of-core” basato su CUDA e contenente una serie di miglioramenti rispetto agli attuali metodi GPU di “ray-casting” di volumi. Le possibilità del sistema sono dimostrate attraverso l’esplorazione interattiva di dataset di 64-GVoxel su un display di tipo light-field da 35-MPixel pilotato da un cluster di PC