Compressed Neighbour Lists for SPH

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dc.contributor.authorBand, Stefanen_US
dc.contributor.authorGissler, Christophen_US
dc.contributor.authorTeschner, Matthiasen_US
dc.contributor.editorBenes, Bedrich and Hauser, Helwigen_US
dc.date.accessioned2020-05-22T12:24:46Z
dc.date.available2020-05-22T12:24:46Z
dc.date.issued2020
dc.description.abstractWe propose a novel compression scheme to store neighbour lists for iterative solvers that employ Smoothed Particle Hydrodynamics (SPH). The compression scheme is inspired by Stream VByte, but uses a non‐linear mapping from data to data bytes, yielding memory savings of up to 87%. It is part of a novel variant of the Cell‐Linked‐List (CLL) concept that is inspired by compact hashing with an improved processing of the cell‐particle relations. We show that the resulting neighbour search outperforms compact hashing in terms of speed and memory consumption. Divergence‐Free SPH (DFSPH) scenarios with up to 1.3 billion SPH particles can be processed on a 24‐core PC using 172 GB of memory. Scenes with more than 7 billion SPH particles can be processed in a Message Passing Interface (MPI) environment with 112 cores and 880 GB of RAM. The neighbour search is also useful for interactive applications. A DFSPH simulation step for up to 0.2 million particles can be computed in less than 40 ms on a 12‐core PC.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13890
dc.identifier.issn1467-8659
dc.identifier.pages531-542
dc.identifier.urihttps://doi.org/10.1111/cgf.13890
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13890
dc.publisher© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltden_US
dc.subjectphysically based animation
dc.subjectdata compression
dc.subjectfluid modelling
dc.subjectsmoothed particle hydrodynamics
dc.subjectI.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism – Animation; • Computing methodologies → Physical simulation
dc.subjectMassively parallel and high‐performance simulations
dc.titleCompressed Neighbour Lists for SPHen_US
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