Det här arbetet har gått ut på att jämföra två algoritmer för bildbaserad rendering. Båda algoritmerna använder två bilder som spelats in med formatet MultiView plus depth för att rendera nya mellanliggande vyer av en tredimensionell scen. De tvådimensionella bilderna är kompletterade med djupvärden för varje bildpunkt. Renderingen kan då utföras genom perspektivriktiga transformationer där alla bildpunkters nya positioner projiceras individuellt. I samband med renderingen behöver bland annat mätfel i de ursprungliga bilderna samt skymda partier hanteras. Algoritm I gör det delvis genom utjämning av skarvararna mellan bildernas bidrag till den nya vyn. Algoritm II bygger på att bilderna delas upp i lager där de lager som ansetts vara säkra prioriteras framför lager som har bedömts vara mer riskabla. Algoritmerna har implementerats i Matlab och algoritm II har modifierats genom kompletteringar av dess regler för prioriteringen av lagren till mer komplicerade scener. Algoritm II har visat sig vara bättre på att bevara detaljer i de renderade vyerna och håller en jämnare hastighet vid renderingarna. Den ger även högre och jämnare resultat vid jämförelse med kvalitetsmåttet PSNR men vid jämförelser med MSSIM har den däremot fått något lägre värden. De ytterligare stegen vid renderingen har även ökat renderingstiderna med upp till 40 % jämfört med algoritm I. Författaren ger förslag på områden för fortsatt utveckling av algoritm II. Till exempel bör algoritmen testas vidare för att avgöra om de använda gränsvärdena är generella eller om de måste anpassas till olika scener. / This thesis has been aimed at comparing two algorithms for image-based renderings. Both algorithms uses two images recorded with the MultiView plus depth format, to render new intermediate views of a three-dimensional scene. The two-dimensional images extensions with depth values for each pixel, makes it possible to perform the image warping as perspective projections of all individually pixels to their new positions. During rendering, such as measurement error in the original images and occlusions has to be handled. Algorithm I is partly based on smoothening the joints between the contributions from the two images to the novel view. Algorithm II divides the images into layers, in which layers consid-ered safe has priority over layers that have been defined as more risky. The algorithms have been implemented in Matlab and algorithm II has been modified through additions to the priority rules for the layers to more complex scenes. Algorithm II has proven to be better at preserving the details in the rendered views, and maintains a less varying speed when rendering. It also provides higher and more consistent PSNR values, but in comparison using MSSIM the values are slightly lower. The additional steps have also increased the rendering times by up to 40 % compared to algorithm I. The author suggests areas for further development of algorithm II. For example, the algorithm should be tested further to determine if the used thresholds are general or whether they must be adapted to different scenes.

Graphics Processing Units (GPUs) have become a popular platform for executing general purpose (i.e., non-graphics) applications. To run efficiently on a GPU, applications must be parallelized into many threads, each of which performs the same task but operates on different data (i.e., data parallelism). Previous work has shown that some applications experience significant speedup when executed on a GPU instead of a CPU. The applications that benefit most tend to have certain characteristics such as high computational intensity, regular control-flow and memory access patterns, and little to no communication among threads. However, not all parallel applications have these characteristics. Applications with a more balanced compute to memory ratio, divergent control flow, irregular memory accesses, and/or frequent communication (i.e., not-so-regular applications) will not take full advantage of the GPU's resources, resulting in performance far short of what could be delivered. The goal of this dissertation is to enhance the GPU architecture to better handle not-so-regular parallelism. This is accomplished in two parts. First, I analyze a diverse set of data parallel applications that suffer from divergent control-flow and/or significant stall time due to memory. I propose two microarchitectural enhancements to the GPU called the Large Warp Microarchitecture and Two-Level Warp Scheduling to address these problems respectively. When combined, these mechanisms increase performance by 19% on average. Second, I examine one of the most important and fundamental applications in computing: database search. Database search is an excellent example of an application that is rich in parallelism, but rife with not-so-regular characteristics. I propose enhancements to the GPU architecture including new instructions that improve intra-warp thread communication and decision making, and also a row-buffer locality hint bit to better handle the irregular memory access patterns of index-based tree search. These proposals improve performance by 21% for full table scans, and 39% for index-based search. The result of this dissertation is an enhanced GPU architecture that better handles not-so-regular parallelism. This increases the scope of applications that run efficiently on the GPU, making it a more viable platform not only for current parallel workloads such as databases, but also for future and emerging parallel applications. / text

abstract: With the massive multithreading execution feature, graphics processing units (GPUs) have been widely deployed to accelerate general-purpose parallel workloads (GPGPUs). However, using GPUs to accelerate computation does not always gain good performance improvement. This is mainly due to three inefficiencies in modern GPU and system architectures. First, not all parallel threads have a uniform amount of workload to fully utilize GPU’s computation ability, leading to a sub-optimal performance problem, called warp criticality. To mitigate the degree of warp criticality, I propose a Criticality-Aware Warp Acceleration mechanism, called CAWA. CAWA predicts and accelerates the critical warp execution by allocating larger execution time slices and additional cache resources to the critical warp. The evaluation result shows that with CAWA, GPUs can achieve an average of 1.23x speedup. Second, the shared cache storage in GPUs is often insufficient to accommodate demands of the large number of concurrent threads. As a result, cache thrashing is commonly experienced in GPU’s cache memories, particularly in the L1 data caches. To alleviate the cache contention and thrashing problem, I develop an instruction aware Control Loop Based Adaptive Bypassing algorithm, called Ctrl-C. Ctrl-C learns the cache reuse behavior and bypasses a portion of memory requests with the help of feedback control loops. The evaluation result shows that Ctrl-C can effectively improve cache utilization in GPUs and achieve an average of 1.42x speedup for cache sensitive GPGPU workloads. Finally, GPU workloads and the co-located processes running on the host chip multiprocessor (CMP) in a heterogeneous system setup can contend for memory resources in multiple levels, resulting in significant performance degradation. To maximize the system throughput and balance the performance degradation of all co-located applications, I design a scalable performance degradation predictor specifically for heterogeneous systems, called HeteroPDP. HeteroPDP predicts the application execution time and schedules OpenCL workloads to run on different devices based on the optimization goal. The evaluation result shows HeteroPDP can improve the system fairness from 24% to 65% when an OpenCL application is co-located with other processes, and gain an additional 50% speedup compared with always offloading the OpenCL workload to GPUs. In summary, this dissertation aims to provide insights for the future microarchitecture and system architecture designs by identifying, analyzing, and addressing three critical performance problems in modern GPUs. / Dissertation/Thesis / Doctoral Dissertation Computer Engineering 2017

My degree project aims to create a set of furniture and space which all “warped” by the voices of my beloved family member. I investigated how to record and translate the voices and materialize them into furniture. I processed the emotion of missing my family by materializing their voices through my “voice embedding methods.” Which I translate voices into form.  My “warped” space aims to reflect the power of human emotions. The voice curves that I extract from the “voice warping method” are rich in information and emotions. I want this “warping complexity” to question the ideology of the clean and empty “ideal space,” which is the tendency in today’s interior architecture and furniture design.

[pt] Esta de tese de doutorado apresenta soluções para a integração entre os algoritmos de Shear-Warp e de Z-Buffer, visando a criação de cenas compostas de dados volumétricos e modelos poligonais opacos e/ou transparentes. A renderização volumétrica baseada na fatoração Shear- Warp é eficiente para a realização das etapas de projeção e composição dos voxels. Ela trabalha de forma coerente com a ordenação das fatias do volume e pode ser naturalmente integrada ao algoritmo de Z-Buffer para a combinação de modelos poligonais. São propostos vários algoritmos para a combinação de dados volumétricos e modelos poligonais visando reduzir o efeito de aliasing introduzido durante o processo de reamostragem do modelo poligo nal. São apresentados testes e resultados que dão suporte às conclusões apresentadas sob o ponto de vista de qualidade de imagem e tempo de processamento.

Football fans do not have the time to watch every game in its entirety and need an effective solution that summarizes them the story of the game. Human-generated summaries are often too short, requiring time and resources to create. We utilize the advantages of Interactive TV to create an automatic football summarization service that is cohesive, provides context, covers the necessary plays, and is concise. First, we construct a degree of interest function that ranks each play based on detailed, play-by-play game events as well as viewing statistics collected from an interactive viewing environment. This allows us to select the plays that are important to the game as well as those that are interesting to the viewer. Second, we create a visual transition that shows the progress of the ball whenever plays are skipped, allowing the viewer to understand the context of each play within the summary. Third, we enable interactive controls that allow viewers to manipulate the summary and delve deeper into the actual game whenever they wish. We validate our solution through two user studies—one to ensure that our degree of interest function selects the plays that are most interesting to the viewer, and the other to show that our transitions and interactive controls provide a better understanding of the game. We conclude that our summary solution is effective at conveying the story of a football game.

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