Parallel Generation of Architecture on the GPU

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dc.contributor.authorSteinberger, Markusen_US
dc.contributor.authorKenzel, Michaelen_US
dc.contributor.authorKainz, Bernharden_US
dc.contributor.authorMüller, Jörgen_US
dc.contributor.authorWonka, Peteren_US
dc.contributor.authorSchmalstieg, Dieteren_US
dc.contributor.editorB. Levy and J. Kautzen_US
dc.date.accessioned2015-03-03T12:26:33Z
dc.date.available2015-03-03T12:26:33Z
dc.date.issued2014en_US
dc.description.abstractIn this paper, we present a novel approach for the parallel evaluation of procedural shape grammars on the graphics processing unit (GPU). Unlike previous approaches that are either limited in the kind of shapes they allow, the amount of parallelism they can take advantage of, or both, our method supports state of the art procedural modeling including stochasticity and context-sensitivity. To increase parallelism, we explicitly express independence in the grammar, reduce inter-rule dependencies required for context-sensitive evaluation, and introduce intra-rule parallelism. Our rule scheduling scheme avoids unnecessary back and forth between CPU and GPU and reduces round trips to slow global memory by dynamically grouping rules in on-chip shared memory. Our GPU shape grammar implementation is multiple orders of magnitude faster than the standard in CPU-based rule evaluation, while offering equal expressive power. In comparison to the state of the art in GPU shape grammar derivation, our approach is nearly 50 times faster, while adding support for geometric context-sensitivity.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12312en_US
dc.publisherThe Eurographics Association and John Wiley and Sons Ltd.en_US
dc.titleParallel Generation of Architecture on the GPUen_US
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33-Issue 2
Full Papers 2014 - CGF 33-Issue 2