[pt] Na visualização de campos escalares de dados volumétricos, o uso de seções de corte é uma técnica eficaz para se inspecionar a variação do campo no interior do domínio. A técnica de visualização consiste em mapear sobre a superfície da seção de corte um mapa de cores, o qual representa a variação do campo escalar na interseção da superfície com o volume. Este trabalho propõe um método eficiente para o mapeamento de campos escalares de malhas não estruturadas em seções de corte arbitrárias. Trata-se de um método de renderização direta (a interseção da superfície com o modelo não é extraída) que usa a GPU para garantir bom desempenho. A idéia básica do método proposto é utilizar o rasterizador da placa gráfica para gerar os fragmentos da superfície de corte e calcular a interseção de cada fragmento com o modelo em GPU. Para isso, é necessário testar a localização de cada fragmento na malha não estruturada de maneira eficiente. Como estrutura de aceleração, foram testadas três variações de grades regulares para armazenar os elementos (células) da malha, e cada elemento é representado pela lista de planos de suas faces, facilitando o teste de pertinência fragmento-elemento. Uma vez determinado o elemento que contém o fragmento, são aplicados procedimentos para interpolar o campo escalar e para identificar se o fragmento está próximo à fronteira do elemento, a fim de representar o aramado (wireframe) da malha na superfície de corte. Resultados obtidos demonstram a eficácia e a eficiência do método proposto. / [en] For the visualization of scalar fields in volume data, the use of cross sections is an effective technique to inspect the field variation inside the domain. The technique consists in mapping, on the cross section surfaces, a colormap that represents the scalar field on the surfasse-volume intersection. In this work, we propose an efficient method for mapping scalar fields of unstructured meshes on arbitrary cross sections. It is a direct-rendering method (the intersection of the surface and the model is not extracted) that uses GPU to ensure efficiency. The basic idea is to use the graphics rasterizer to generate the fragments of the cross-section surface and to compute the intersection of each fragment with the model. For this, it is necessary to test the location of each fragment with respect to the unstructured mesh in an efficient way. As acceleration data structure, we tested three variations of regular grids to store the elements (cells) of the mesh, and each elemento is represented by the list of face planes, easing the in-out test between fragments and elements. Once the element that contains the fragment is determined, it is applied procedures to interpolate the scalar field and to check if the fragment is close to the element boundary, to reveal the mesh wireframe on the surface. Achieved results demonstrate the effectiveness and the efficiency of the proposed method.

[pt] O primeiro estágio na linha de produção de um sistema de geração procedural de cidades é, tipicamente, a geração da malha rodoviária. Este trabalho apresenta um algoritmo para a geração de malhas rodoviárias em paralelo na GPU usando um modelo de execução baseado em filas de trabalho. Esse algoritmo recebe parâmetros declarativos, juntamente com mapas geográficos e sócio estatísticos, e produz uma representação em alto nível de uma malha rodoviária urbana. / [en] The first stage in the pipeline of a procedural city generation system is typically the generation of the road network. This work presents a parallel algorithm for road networks generation on the GPU, using a work-queue based execution model. This algorithm receives declarative parameters along with geographic and socio-statistical maps and produces a high level representation of an urban road network.

This thesis presents a two-phase liquid-solid numerical model using Smoothed Particle Hydrodynamics (SPH). The scheme is developed for multi-phase flows in industrial tanks containing sediment used in the nuclear industry for decommissioning. These two-phase liquid-sediments flows feature a changing interfacial profile, large deformations and fragmentation of the interface with internal jets generating resuspension of the solid phase. SPH is a meshless Lagrangian discretization scheme whose major advantage is the absence of a mesh making the method ideal for interfacial and highly non-linear flows with fragmentation and resuspension. Emphasis has been given to the yield profile and rheological characteristics of the sediment solid phase using a yielding, shear and suspension layer which is needed to predict accurately the erosion phenomena. The numerical SPH scheme is based on the explicit treatment of both phases using Newtonian and non-Newtonian Bingham-type constitutive models. This is supplemented by a yield criterion to predict the onset of yielding of the sediment surface and a suspension model at low volumetric concentrations of sediment solid. The multi-phase model has been compared with experimental and 2-D reference numerical models for scour following a dry-bed dam break yielding satisfactory results and improvements over well-known SPH multi-phase models. A 3-D case using more than 4 million particles, that is to the author’s best knowledge one of the largest liquid-sediment SPH simulations, is presented for the first time. The numerical model is accelerated with the use of Graphic Processing Units (GPUs), with massively parallel capabilities. With the adoption of a multi-phase model the computational requirements increase due to extra arithmetic operations required to resolve both phases and the additional memory requirements for storing a second phase in the device memory. The open source weakly compressible SPH solver DualSPHysics was chosen as the platform for both CPU and GPU implementations. The implementation and optimisation of the multi-phase GPU code achieved a speed up of over 50 compared to a single thread serial code. Prior to this thesis, large resolution liquid-solid simulations were prohibitive and 3-D simulations with millions of particles were unfeasible unless variable particle resolution was employed. Finally, the thesis addresses the challenging problem of enforcing wall boundary conditions in SPH with a novel extension of an existing Modified Virtual Boundary Particle (MVBP) technique. In contrast to the MVBP method, the extended MVBP (eMVBP) boundary condition guarantees that arbitrarily complex domains can be readily discretized ensuring approximate zeroth and first order consistency for all particles whose smoothing kernel support overlaps the boundary. The 2-D eMVBP method has also been extended to 3-D using boundary surfaces discretized into sets of triangular planes to represent the solid wall. Boundary particles are then obtained by translating a full uniform stencil according to the fluid particle position and applying an efficient ray casting algorithm to select particles inside the fluid domain. No special treatment for corners and low computational cost make the method ideal for GPU parallelization. The models are validated for a number of 2-D and 3-D cases, where significantly improved behaviour is obtained in comparison with the conventional boundary techniques. Finally the capability of the numerical scheme to simulate a dam break simulation is also shown in 2-D and 3-D.

In this thesis work we have extended the SkePU framework by designing a new container data structure for the representation of generic two dimensional sparse matrices. Computation on matrices is an integral part of many scientific and engineering problems. Sometimes it is unnecessary to perform costly operations on zero entries of the matrix. If the number of zeroes is relatively large then a requirement for more efficient data structure arises. Beyond the sparse matrix representation, we propose an algorithm to judge the condition where computation on sparse matrices is more beneficial in terms of execution time for an ongoing computation and to adapt a matrix's state accordingly, which is the main concern of this thesis work. We present and implement an approach to switch automatically between two data container types dynamically inside the SkePU framework for a multi-core GPU-based heterogeneous system. The new sparse matrix data container supports all SkePU skeletons and nearly all SkePU operations. We provide compression and decompression algorithms from dense matrix to sparse matrix and vice versa on CPU and GPUs using SkePU data parallel skeletons. We have also implemented a context aware switching mechanism in order to switch between two data container types on the CPU or the GPU. A multi-state matrix representation, and selection on demand is also made possible. In order to evaluate and test effectiveness and efficiency of our extension to the SkePU framework, we have considered Matrix-Vector Multiplication as our benchmark program because iterative solvers like Conjugate Gradient and Generalized Minimum Residual use Sparse Matrix-Vector Multiplication as their basic operation. Through our benchmark program we have demonstrated adaptive switching between two data container types, implementation selection between CUDA and OpenMP, and converting the data structure depending on the density of non-zeroes in a matrix. Our experiments on GPU-based architectures show that our automatic switching mechanism adapts with the fastest SkePU implementation variant, and has a limited training cost.

[pt] A visualização eficiente de grandes modelos digitais de elevação continua sendo um desafio para aplicações em tempo real. O uso direto de novas tecnologias de triangulação em placas gráficas tem uma aplicabilidade limitada no gerenciamento dos níveis de detalhe para grandes modelos. Embora o hardware gráfico seja capaz de controlar a resolução do modelo de um modo bastante eficiente, todos os dados devem estar em memória. Isso compromete a escalabilidade de soluções simples baseadas em GPU para controlar o nível de detalhe. Neste trabalho, é proposto um novo algoritmo eficiente e escalável para lidar com grandes modelos digitais de elevação. A proposta combina efetivamente a triangulação em GPU com a gerência de ladrilhos em CPU, tirando proveito da capacidade de processamento da GPU ao mesmo tempo que mantém o uso de memória gráfica dentro dos limites práticos. Também é proposta uma técnica para gerenciar o nível de detalhe da imagem aérea mapeada sobre o modelo de elevação como texturas. Ambas gerências de níveis de detalhe (geometria e textura) executam separadamente, e os ladrilhos são combinados sem a necessidade de carregar qualquer dado adicional. O gerenciamento de níveis de detalhe é então estendido para lidar com modelos com bordas irregulares e buracos. / [en] Efficient rendering of large digital elevation models remains as a challenge for real-time applications. The direct use of hardware tessellation has limited applicability for managing level of detail of large models. Although the graphics hardware is capable of controlling the resolution of patches in a very efficient manner, the whole patch data must be loaded in memory. This compromises the scalability of GPU-based naive solutions for controlling level of detail. In this work, we propose an efficient and scalable new algorithm for large digital elevation models. Our proposal effectively combines GPU tessellation with CPU tile management, taking full advantage of GPU processing capabilities while maintaining graphics-memory use under practical limits. We also propose a technique to manage level of detail of aerial imagery mapped on top of elevation models as textures. Both geometry and texture level of detail management run independently, and tiles are combined with no need to load extra data. The proposed level of detail management is then extended to handle model with irregular border and holes.

Bio-pharmaceutical industry is a vast growing market and recent recommendations of the Food and Drug Administration have put a large emphasis on the characterization of biological processes and models. As a consequence, there is a high incentive on developing modern sensors in order to more accurately monitor and control processes. In that way, Digital Holographic Microscopy (DHM) presents unique features thanks to the refocusing and quantitative phase contrast imaging capabilities. In this thesis we investigate the usage of DHM to monitor yeast cultures that are often used in both the bio-pharmaceutical and bread industries and lay the basis of a methodological framework for the study of in-line cell cultures in the context of process control. We begin with a description of Digital Holography and the microscopy setup used in the thesis as well as a detailed explanation of the image processing required to extract the holographic data and its implementation on GPU with some speed execution figures given for three popular programming paradigms. We then describe the flow setup used and infer the limitations on the dynamic range of the technique due to both Poisson statistics and overlapping phenomena. Finally, we describe an algorithm that extracts the cells position, count and morphological information such as the size, aspect ratio, circularity and refraction index. Some experimental results are presented for yeasts before drawing a general overview of the technology and its dependencies. We further end with some conclusions concerning the technology and a brief comparison with existing competitors. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

[pt] Técnicas de mapeamento de rugosidade são amplamente utilizadas para simular detalhes estruturais de superfícies tridimensionais com o intuito de aumentar a qualidade visual e compensar o baixo detalhamento geométrico usualmente aplicado aos modelos enviados à GPU por questões de desempenho. Avanços recentes no pipeline de renderização permitiram a geração massiva de vértices no hardware gráfico através do recurso de tesselação, oferecendo aos desenvolvedores uma poderosa ferramenta para controle do nível de detalhes de objetos. Este trabalho apresenta uma técnica para o detalhamento geométrico de modelos utilizando tesselação em hardware, baseada tanto em mapas précomputados quanto em dados de deslocamento gerados inteiramente na GPU por meio de técnicas de texturas procedimentais. Análises de desempenho e qualidade visual demonstram as vantagens do método proposto em relação a uma técnica de detalhamento baseada em imagens que é utilizada frequentemente em jogos eletrônicos para enriquecimento da qualidade visual de seus ambientes. / [en] Bump mapping techniques are widely used to simulate structural details of tridimensional surfaces in order to improve visual quality and compensate for the low geometric detailing generally applied to models sent to the GPU due to performance issues. Recent advances in the rendering pipeline enabled the massive generation of vertex data in the graphics hardware by means of the tessellation feature, providing developers with a powerful tool to control the meshes’ level of details. The present work proposes a technique for geometric detailing of models using hardware tessellation, both based on pre-computed depth maps and on displacement data generated entirely on the GPU through procedural textures techniques. Performance and visual quality analysis demonstrates the advantages of the proposed method in relation to an image-based technique commonly used in videogames for enhancing the visual quality of the environments.

Automatical electrochemical measurements are sources of large data sets intended for further analysis. This work deals with classification, evaluation and processing of electrochemical signals using artificial neural networks. Due to high dimensionality of input data, an autoassociative neural network (AANN) is used in this work. This type of network performs dimensionality reduction via filtering the input data into relatively small number of principal parameters at the bottleneck output. These extracted parameters can be used for classification, evaluation and additional modelling of analyzed data trough the reconstructive part of this network. Furthermore, this work deals with implementation of a feedforward neural network in OpenCL language.

This thesis addresses a number of problems in computer vision, image processing, and geometry processing, and presents novel solutions to these problems. The overarching theme of the techniques presented here is a multi-scale approach, leveraging mathematical tools to represent images and surfaces at different scales, and methods that can be adapted from one type of domain (eg., the plane) to another (eg., the sphere). The main problem addressed in this thesis is known as stereo reconstruction: reconstructing the geometry of a scene or object from two or more images of that scene. We develop novel algorithms to do this, which work for both planar and spherical images. By developing a novel way to formulate the notion of disparity for spherical images, we are able effectively adapt our algorithms from planar to spherical images. Our stereo reconstruction algorithm is based on a novel application of distance transforms to multi-scale matching. We use matching information aggregated over multiple scales, and enforce consistency between these scales using distance transforms. We then show how multiple spherical disparity maps can be efficiently and robustly fused using visibility and other geometric constraints. We then show how the reconstructed point clouds can be used to synthesize a realistic sequence of novel views, images from points of view not captured in the input images, in real-time. Along the way to this result, we address some related problems. For example, multi-scale features can be detected in spherical images by convolving those images with a filterbank, generating an overcomplete spherical wavelet representation of the image from which the multiscale features can be extracted. Convolution of spherical images is much more efficient in the spherical harmonic domain than in the spatial domain. Thus, we develop a GPU implementation for fast spherical harmonic transforms and frequency domain convolutions of spherical images. This tool can also be used to detect multi-scale features on geometric surfaces. When we have a point cloud of a surface of a particular class of object, whether generated by stereo reconstruction or by some other modality, we can use statistics and machine learning to more robustly estimate the surface. If we have at our disposal a database of surfaces of a particular type of object, such as the human face, we can compute statistics over this database to constrain the possible shape a new surface of this type can take. We show how a statistical spherical wavelet shape prior can be used to efficiently and robustly reconstruct a face shape from noisy point cloud data, including stereo data.

The rendering of participating media is an interesting and important problem without a simple solution. Yet even among the wide variety of participating media the clouds stand out as an especially difficult case, because of their properties that make their simulation even harder. The work presented in this thesis attempts to provide a solution to this problem, and moreover, to make the proposed method to work in interactive rendering speeds. The main design criteria in designing this method were its physical plausibility and maximal utilization of specific cloud properties which would help to balance the complex nature of clouds. As a result the proposed method builds on the well known photon mapping algorithm, but modifies it in several ways to obtain interactive and temporarily coherent results. This is further helped by designing the method in such a way which allows its implementation on contemporary GPUs, taking advantage of their massively parallel sheer computational power. We implement a prototype of the method in an application that renders a single realistic cloud in interactive framerates, and discuss possible extensions of the proposed technique that would allow its use in various practical industrial applications.