GPU-Parallel Constant-Time Limit Evaluation of Catmull-Clark Solids

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dc.contributor.authorBesler, Sebastianen_US
dc.contributor.authorAltenhofen, Christianen_US
dc.contributor.authorStork, Andréen_US
dc.contributor.authorFellner, Dieter W.en_US
dc.contributor.editorAndres, Bjoern and Campen, Marcel and Sedlmair, Michaelen_US
dc.date.accessioned2021-09-25T16:36:22Z
dc.date.available2021-09-25T16:36:22Z
dc.date.issued2021
dc.description.abstractSubdivision solids, such as Catmull-Clark (CC) solids, are versatile volumetric representation schemes that can be employed for geometric modeling, physically based simulation, and multi-material additive manufacturing. With volumetric limit evaluation still being the performance bottleneck for these applications, we present a massively parallel approach to Altenhofen et al.'s constant-time limit evaluation method for CC solids. Our algorithm exploits the computational power of modern GPUs, while maintaining the mathematical concepts of Altenhofen et al.'s method. Distributing the computations for a single cell across multiple streaming multiprocessors (SMs) increases the utilization of the GPU's resources compared to straightforward parallelization. Specialized compute kernels for different topological configurations optimize shared memory usage and memory access. Our hybrid approach dynamically chooses the best kernel based on the topology and the evaluation parameters, resulting in speedups of between 5.75x and 61.58x compared to a CPU-parallel implementation of Altenhofen et al.'s method.en_US
dc.description.sectionheadersSmooth Surfaces and Volumes
dc.description.seriesinformationVision, Modeling, and Visualization
dc.identifier.doi10.2312/vmv.20211369
dc.identifier.isbn978-3-03868-161-8
dc.identifier.pages35-46
dc.identifier.urihttps://doi.org/10.2312/vmv.20211369
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20211369
dc.publisherThe Eurographics Associationen_US
dc.titleGPU-Parallel Constant-Time Limit Evaluation of Catmull-Clark Solidsen_US
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