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dc.contributor.authorWeinzierl, Tobias
dc.contributor.authorBader, Michael
dc.contributor.authorUnterweger, Kristof
dc.contributor.authorWittmann, Roland
dc.date.accessioned2016-02-25T12:44:23Z
dc.date.available2016-02-25T12:44:23Z
dc.date.issued2014-09-29
dc.identifier.citationWeinzierl T, Bader M, Unterweger K, Wittmann R (2014) Block Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves. Parallel Process Lett 24: 1441006. Available: http://dx.doi.org/10.1142/S0129626414410060.
dc.identifier.issn0129-6264
dc.identifier.issn1793-642X
dc.identifier.doi10.1142/S0129626414410060
dc.identifier.urihttp://hdl.handle.net/10754/597685
dc.description.abstract© 2014 World Scientific Publishing Company. Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Even though they directly yield a mesh, it is often computationally reasonable to embed regular Cartesian blocks into their leaves. This promotes stencils working on homogeneous data chunks. The choice of a proper block size is sensitive. While large block sizes foster loop parallelism and vectorisation, they restrict the adaptivity's granularity and hence increase the memory footprint and lower the numerical accuracy per byte. In the present paper, we therefore use a multiscale spacetree-block coupling admitting blocks on all spacetree nodes. We propose to find sets of blocks on the finest scale throughout the simulation and to replace them by fused big blocks. Such a replacement strategy can pick up hardware characteristics, i.e. which block size yields the highest throughput, while the dynamic adaptivity of the fine grid mesh is not constrained - applications can work with fine granular blocks. We study the fusion with a state-of-the-art shallow water solver at hands of an Intel Sandy Bridge and a Xeon Phi processor where we anticipate their reaction to selected block optimisation and vectorisation.
dc.description.sponsorshipTobias Weinzierl appreciates the support of the School of Engineering and Computing Sciences and in particular Tomasz Koziara at Durham University for providing
dc.publisherWorld Scientific Pub Co Pte Lt
dc.subjectAdaptive Cartesian meshes
dc.subjectBlock fusion
dc.subjectShallow water
dc.subjectShared memory parallelisation
dc.subjectSpacetrees
dc.subjectVectorisation
dc.titleBlock Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves
dc.typeArticle
dc.identifier.journalParallel Processing Letters
dc.contributor.institutionUniversity of Durham, Durham, United Kingdom
dc.contributor.institutionTechnische Universitat Munchen, Munich, Germany
kaust.grant.numberUK-c0020
dc.date.published-online2014-09-29
dc.date.published-print2014-09


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