Browsing by Author "Gomes, Abel"

Now showing 1 - 6 of 6
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    BEDS: Uma Estrutura de Dados para Malhas Triangulares
    (The Eurographics Association, 2021) Silva, Frutuoso; Gomes, Abel; Coelho, António and Cláudio, Ana Paula
    As malhas triangulares tem um papel fundamental na ComputafiiO Grafica. Este artigo apresenta uma nova estrutura de dados geometrica para representar malhas triangulares, designada de Butte,jly Edge Data Structure ( BEDS). Esta estrutura de dados representa apenas os vertices e as arestas, sendo as faces representadas impli- citamente por vertices. Esta estrutura de dados implementa uma representarao CJ para malhas triangulares, o que significa que tem dois acessos directos e sete indirectos para aceder a toda a informarao topol6gica da malha. Apesar disso, permite o acesso as faces directamente atra ves das arestas como um conjunto de tres vertices. Esta estrutura de dados permite tambem representar malhas triangulares niio-manifold.
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    Fast CUDA-Based Triangulation of Molecular Surfaces
    (The Eurographics Association, 2021) Dias, Sérgio; Gomes, Abel; Coelho, António and Cláudio, Ana Paula
    Modeling molecular surfaces enables us to extract useful information about interactions with other molecules and measurements of areas and volumes. Over the years many types of algorithms have been developed to represent and rendering molecular surfaces, but all these algorithms have problems related to time performance in triangulating molecular surfaces. One possible solution to solve this problem is using parallel computing systems, but until recently they have been very expensive. Fortunately, the appearance of the new generation of low-cost GPUs with massive computational power opens up an opportunity window to solve this problem. So, in this paper, we present a GPU-based algorithm to speed up the triangulation and rendering of molecular surfaces. Besides we carry out a study that compares a sequential version (CPU) and a parallel version (GPU) of a molecular surface representation using the Marching Cubes (MC) Algorithm.
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    Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey
    (© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Simões, Tiago; Lopes, Daniel; Dias, Sérgio; Fernandes, Francisco; Pereira, João; Jorge, Joaquim; Bajaj, Chandrajit; Gomes, Abel; Chen, Min and Zhang, Hao (Richard)
    Detecting and analysing protein cavities provides significant information about active sites for biological processes (e.g. protein–protein or protein–ligand binding) in molecular graphics and modelling. Using the three‐dimensional (3D) structure of a given protein (i.e. atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution‐based, energy‐based and geometry‐based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere‐, grid‐ and tessellation‐based methods, but also surface‐based, hybrid geometric, consensus and time‐varying methods. Finally, we detail those techniques that have been customized for GPU (graphics processing unit) computing.Detecting and analysing protein cavities provides significant information about active sites for biological processes (e.g. protein–protein or protein–ligand binding) in molecular graphics and modelling. Using the three‐dimensional (3D) structure of a given protein (i.e. atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution‐based, energy‐based and geometry‐based.
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    Linear Solvers for Stable Fluids: GPU vs CPU
    (The Eurographics Association, 2021) Amador, Gonçalo; Gomes, Abel; Coelho, António and Cláudio, Ana Paula
    Fluid simulation has been an active research field in computer graphics for the last 30 years. Stam's stable fluids method, among others, is used for solving equations that govern fluids. This method solves a sparse linear system during the diffusion and move steps, using either relaxation methods (Jacobi, Gauss-Seidel, etc ), Conjugate Gradient (and its variants), or others (not subject of study in this paper). A comparative pe,formance analysis between a parallel GPU-based (using CUDA) algorithm and a serial CPU-based algorithm, in both 2D and 3D, is given with the corresponding implementation of Jacobi (J), Gauss-Seidel (GS) and Conjugate Gradient (CG) solvers.
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    Malhas Segmentadas com Resolução Variável
    (The Eurographics Association, 2020) Rodrigues, Rui S. V.; Morgado, José F. M.; Gomes, Abel; Dias, Paulo and Menezes, Paulo
    As malhas com resolução variável (''multiresolution meshes'') têm sido utilizadas como alternativa à técnica dos LODs em ambientes virtuais e jogos de computador, em que o detalhe da cena depende da distãncia ao observador, bem como na (des)compressão de malhas em tarefas de transferência e transmissão mais célere de malhas através da Internet e da web, o que permite o carregamento progressivo da malha do lado do cliente, que começa com uma malha mais grosseira e termina com uma malha mais refinada. A principal contribuição deste artigo reside na utilização do conceito de multirresolução em malhas segmentadas, em vez de malhas simples (sem segmentação).
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    Reconstrução de Superfícies Trianguladas a partir de Nuvens de Pontos sem Restrições Angulares
    (The Eurographics Association, 2020) Leitão, Gonçalo; Gomes, Abel; Dias, Paulo and Menezes, Paulo
    A reconstrução de uma superfície triangulada a partir de uma nuvem de pontos é um problema difícil de resolver dado depender da forma do objeto original e da densidade dos pontos obtidos pelo dispositivo de aquisição 3D utilizado (scanner). Em grande medida, os algoritmos baseados em expansão da malha que existem na literatura não são bem-sucedidos porque os triângulos são apensos à malha em expansão com base em intervalos angulares que não podem ser ultrapassados. Por contraposição, propõe-se neste artigo um algoritmo que resolve este problema através da conjunção de funções que quantificam três propriedades geométricas fundamentais: coplanaridade, proximidade e regularidade.