Browsing by Subject "Direct volume visualization"

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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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    ItemOpen Access
    Hardware-accelerated direct visualization of unstructured volumetric meshes
    (2022-07) Şahıstan, Alper
    Computational fluid dynamic simulations often produce large clusters of finite ele-ments with non-trivial, non-convex boundaries and uneven distributions among com-pute nodes, posing challenges to compositing during interactive volume rendering. Correct, in-place visualization of such clusters becomes difficult because viewing rays straddle domain boundaries across multiple compute nodes. We propose a GPU-based, scalable, memory-efficient direct volume visualization framework suitable for in situ and post hoc usage. Our approach reduces memory usage of the unstructured volume elements by leveraging an exclusive or-based index reduction scheme and provides fast ray-marching-based traversal without requiring large external data structures built over the elements. Moreover, we present a GPU-optimized deep compositing scheme that allows correct order compositing of intermediate color values accumulated across different ranks that works even for non-convex clusters. Furthermore, we illustrate that we can achieve secondary effects such as shadows and gradient shading using our method for single GPU setups. Our approach scales well on large data-parallel sys-tems and achieves interactive frame rates during visualization. We can interactively render Fun3D Small Mars Lander (14 GB / 798.4 million finite elements) and Huge Mars Lander (111.57 GB / 6.4 billion finite elements) data sets at 14 and 10 frames per second using 72 and 80 GPUs, respectively, on the Frontera supercomputer at The Texas Advanced Computing Center (TACC).