Browsing by Subject "OpenMP"

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    Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP
    (2014) Okuyan, E.; Güdükbay, Uğur
    Direct volume visualization is an important method in many areas, including computational fluid dynamics and medicine. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multicore parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm supports progressive rendering. Wecompared the GPU implementation with the serial and multicore implementations.We observed significant speed-ups that, together with progressive rendering, enables reaching interactive rates for large datasets. © Springer Science+Business Media New York 2013.
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    Peachy parallel assignments (EduPar 2019)
    (Institute of Electrical and Electronics Engineers Inc., 2019) Öztürk, Özcan; Glick, B.; Mache, J.; Bunde, D. P.
    Peachy Parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of assignments includes face recognition, finding the electrical potential of a square wire, and heat diffusion. All of these come with sample assignment sheets and the necessary starter code.
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    Volumetric rendering techniques for scientific visualization
    (2014) Okuyan, Erhan
    Direct volume rendering is widely used in many applications where the inside of a transparent or a partially transparent material should be visualized. We have explored several aspects of the problem. First, we proposed a view-dependent selective refinement scheme in order to reduce the high computational requirements without affecting the image quality significantly. Then, we explored the parallel implementations of direct volume rendering: both on GPU and on multi-core systems. Finally, we used direct volume rendering approaches to create a tool, MaterialVis, to visualize amorphous and/or crystalline materials. Visualization of large volumetric datasets has always been an important problem. Due to the high computational requirements of volume-rendering techniques, achieving interactive rates is a real challenge. We present a selective refinement scheme that dynamically refines the mesh according to the camera parameters. This scheme automatically determines the impact of different parts of the mesh on the output image and refines the mesh accordingly, without needing any user input. The viewdependent refinement scheme uses a progressive mesh representation that is based on an edge collapse-based tetrahedral mesh simplification algorithm. We tested our view-dependent refinement framework on an existing state-of-the-art volume renderer. Thanks to low overhead dynamic view-dependent refinement, we achieve interactive frame rates for rendering common datasets at decent image resolutions. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multi-core parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm support progressive rendering. We compared the GPU implementation with the serial and multi-core implementations. We observed significant speed-ups, that, together with progressive rendering, enabling reaching interactive rates for large datasets. Visualization of materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called MaterialVis. Unlike the existing tools, MaterialVis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. MaterialVis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, MaterialVis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography.