A More Efficient Parallel Method For Neighbour Search Using CUDA

dc.contributor.authorMorillo, Danielen_US
dc.contributor.authorCarmona, Ricardoen_US
dc.contributor.authorPerea, Juan J.en_US
dc.contributor.authorCordero, Juan M.en_US
dc.contributor.editorFabrice Jaillet and Florence Zara and Gabriel Zachmannen_US
dc.date.accessioned2015-11-04T08:42:07Z
dc.date.available2015-11-04T08:42:07Z
dc.date.issued2015en_US
dc.description.abstractIn particle systems simulation, the procedure of neighbour searching is usually a bottleneck in terms of computational cost. Several techniques have been developed to solve this problem; one of particular interest is the cell-based spatial division, where each cell is tagged by a hash function. One of the most useful features of this technique is that it can be easily parallelized to reduce computational costs. However, the parallelizing process has some drawbacks associated to data memory management. Also, when parallelizing neighbour search, the location of neighbouring particles between adjacent cells is also costly. To solve these shortcomings we have developed a method that reduces the search space by considering the relative position of each particles in its own cell. This method, parallelized using CUDA, shows improvements in processing time and memory management over other ''standard'' spatial division techniques.en_US
dc.description.sectionheadersModel Analysis & Techniquesen_US
dc.description.seriesinformationWorkshop on Virtual Reality Interaction and Physical Simulationen_US
dc.identifier.doi10.2312/vriphys.20151339en_US
dc.identifier.isbn978-3-905674-98-9en_US
dc.identifier.pages101-109en_US
dc.identifier.urihttps://doi.org/10.2312/vriphys.20151339en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectAnimationen_US
dc.subjectI.6.8 [Computer Graphics]en_US
dc.subjectTypes of Simulationen_US
dc.subjectParallelen_US
dc.titleA More Efficient Parallel Method For Neighbour Search Using CUDAen_US
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