Accelerating Hash Grid and Screen-Space Photon Mapping in 3D Interactive Applications with OpenCL

Achieving interactive and realistic rendering is only possible with a combination of rendering algorithms, rendering pipelines, multi-core hardware, and parallelization APIs. This project explores and implements two photon mapping pipelines based on the work of Mara et. al [5] and Singh et. al [7] to achieve interactive rendering performance for a set of simple scenes using OpenCL and C++ to work with a GPU. In particular, both a 3D hash grid and a screen-space tiling algorithm are parallelized to accelerate photon lookup in order to compute direct and indirect lighting on visible surfaces in a scene. By using OpenCL with photon mapping interactive renderings of scenes were produced and updated live as a user moved a virtual camera. This work with OpenCL paved the way for developing a raytracing pipeline in OpenGL and for future work on the latest research in realtime realistic rendering

GPU acceleration of time-domain fluorescence lifetime imaging

Fluorescence lifetime imaging microscopy (FLIM) plays a significant role in biological sciences, chemistry, and medical research. We propose a Graphic Processing Units (GPUs) based FLIM analysis tool suitable for high-speed and flexible time-domain FLIM applications. With a large number of parallel processors, GPUs can significantly speed up lifetime calculations compared to CPU-OpenMP (parallel computing with multiple CPU cores) based analysis. We demonstrate how to implement and optimize FLIM algorithms on GPUs for both iterative and non-iterative FLIM analysis algorithms. The implemented algorithms have been tested on both synthesized and experimental FLIM data. The results show that at the same precision the GPU analysis can be up to 24-fold faster than its CPU-OpenMP counterpart. This means that even for high precision but time-consuming iterative FLIM algorithms, GPUs enable fast or even real-time analysis

Efficient From-Point Visibility for Global Illumination in Virtual Scenes with Participating Media

Sichtbarkeitsbestimmung ist einer der fundamentalen Bausteine fotorealistischer Bildsynthese. Da die Berechnung der Sichtbarkeit allerdings äußerst kostspielig zu berechnen ist, wird nahezu die gesamte Berechnungszeit darauf verwendet. In dieser Arbeit stellen wir neue Methoden zur Speicherung, Berechnung und Approximation von Sichtbarkeit in Szenen mit streuenden Medien vor, die die Berechnung erheblich beschleunigen, dabei trotzdem qualitativ hochwertige und artefaktfreie Ergebnisse liefern

Efficient multi-bounce lightmap creation using GPU forward mapping

Computer graphics can nowadays produce images in realtime that are hard to distinguish from photos of a real scene. One of the most important aspects to achieve this is the interaction of light with materials in the virtual scene. The lighting computation can be separated in two different parts. The first part is concerned with the direct illumination that is applied to all surfaces lit by a light source; algorithms related to this have been greatly improved over the last decades and together with the improvements of the graphics hardware can now produce realistic effects. The second aspect is about the indirect illumination which describes the multiple reflections of light from each surface. In reality, light that hits a surface is never fully absorbed, but instead reflected back into the scene. And even this reflected light is then reflected again and again until its energy is depleted. These multiple reflections make indirect illumination very computationally expensive. The first problem regarding indirect illumination is therefore, how it can be simplified to compute it faster. Another question concerning indirect illumination is, where to compute it. It can either be computed in the fixed image that is created when rendering the scene or it can be stored in a light map. The drawback of the first approach is, that the results need to be recomputed for every frame in which the camera changed. The second approach, on the other hand, is already used for a long time. Once a static scene has been set up, the lighting situation is computed regardless of the time it takes and the result is then stored into a light map. This is a texture atlas for the scene in which each surface point in the virtual scene has exactly one surface point in the 2D texture atlas. When displaying the scene with this approach, the indirect illumination does not need to be recomputed, but is simply sampled from the light map. The main contribution of this thesis is the development of a technique that computes the indirect illumination solution for a scene at interactive rates and stores the result into a light atlas for visualizing it. To achieve this, we overcome two main obstacles. First, we need to be able to quickly project data from any given camera configuration into the parts of the texture that are currently used for visualizing the 3D scene. Since our approach for computing and storing indirect illumination requires a huge amount of these projections, it needs to be as fast as possible. Therefore, we introduce a technique that does this projection entirely on the graphics card with a single draw call. Second, the reflections of light into the scene need to be computed quickly. Therefore, we separate the computation into two steps, one that quickly approximates the spreading of the light into the scene and a second one that computes the visually smooth final result using the aforementioned projection technique. The final technique computes the indirect illumination at interactive rates even for big scenes. It is furthermore very flexible to let the user choose between high quality results or fast computations. This allows the method to be used for quickly editing the lighting situation with high speed previews and then computing the final result in perfect quality at still interactive rates. The technique introduced for projecting data into the texture atlas is in itself highly flexible and also allows for fast painting onto objects and projecting data onto it, considering all perspective distortions and self-occlusions

Sparse Volumetric Deformation

Volume rendering is becoming increasingly popular as applications require realistic solid shape representations with seamless texture mapping and accurate filtering. However rendering sparse volumetric data is difficult because of the limited memory and processing capabilities of current hardware. To address these limitations, the volumetric information can be stored at progressive resolutions in the hierarchical branches of a tree structure, and sampled according to the region of interest. This means that only a partial region of the full dataset is processed, and therefore massive volumetric scenes can be rendered efficiently. The problem with this approach is that it currently only supports static scenes. This is because it is difficult to accurately deform massive amounts of volume elements and reconstruct the scene hierarchy in real-time. Another problem is that deformation operations distort the shape where more than one volume element tries to occupy the same location, and similarly gaps occur where deformation stretches the elements further than one discrete location. It is also challenging to efficiently support sophisticated deformations at hierarchical resolutions, such as character skinning or physically based animation. These types of deformation are expensive and require a control structure (for example a cage or skeleton) that maps to a set of features to accelerate the deformation process. The problems with this technique are that the varying volume hierarchy reflects different feature sizes, and manipulating the features at the original resolution is too expensive; therefore the control structure must also hierarchically capture features according to the varying volumetric resolution. This thesis investigates the area of deforming and rendering massive amounts of dynamic volumetric content. The proposed approach efficiently deforms hierarchical volume elements without introducing artifacts and supports both ray casting and rasterization renderers. This enables light transport to be modeled both accurately and efficiently with applications in the fields of real-time rendering and computer animation. Sophisticated volumetric deformation, including character animation, is also supported in real-time. This is achieved by automatically generating a control skeleton which is mapped to the varying feature resolution of the volume hierarchy. The output deformations are demonstrated in massive dynamic volumetric scenes

Hierarchical N-Body problem on graphics processor unit

Galactic simulation is an important cosmological computation, and represents a classical N-body problem suitable for implementation on vector processors. Barnes-Hut algorithm is a hierarchical N-Body method used to simulate such galactic evolution systems. Stream processing architectures expose data locality and concurrency available in multimedia applications. On the other hand, there are numerous compute-intensive scientific or engineering applications that can potentially benefit from such computational and communication models. These applications are traditionally implemented on vector processors. Stream architecture based graphics processor units (GPUs) present a novel computational alternative for efficiently implementing such high-performance applications. Rendering on a stream architecture sustains high performance, while user-programmable modules allow implementing complex algorithms efficiently. GPUs have evolved over the years, from being fixed-function pipelines to user programmable processors. In this thesis, we focus on the implementation of Barnes-Hut algorithm on typical current-generation programmable GPUs. We exploit computation and communication requirements present in Barnes-Hut algorithm to expose their suitability for user-programmable GPUs. Our implementation of the Barnes-Hut algorithm is formulated as a fragment shader targeting the selected GPU. We discuss implementation details, design issues, results, and challenges encountered in programming the fragment shader