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dc.contributor.authorKerbl, Bernharden_US
dc.contributor.authorKenzel, Michaelen_US
dc.contributor.authorSchmalstieg, Dieteren_US
dc.contributor.authorSteinberger, Markusen_US
dc.contributor.editorVlastimil Havran and Karthik Vaiyanathanen_US
dc.date.accessioned2017-12-06T19:47:36Z
dc.date.available2017-12-06T19:47:36Z
dc.date.issued2017
dc.identifier.isbn978-1-4503-5101-0
dc.identifier.issn2079-8679
dc.identifier.urihttp://dx.doi.org/10.1145/3105762.3105777
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3105762-3105777
dc.description.abstractTo e ectively utilize an ever increasing number of processors during parallel rendering, hardware and so ware designers rely on sophisticated load balancing strategies. While dynamic load balancing is a powerful solution, it requires complex work distribution and synchronization mechanisms. Graphics hardware manufacturers have opted to employ static load balancing strategies instead. Speci cally, triangle data is distributed to processors based on its overlap with screenspace tiles arranged in a xed pa ern. While the current strategy of using simple pa erns for a small number of fast rasterizers achieves formidable performance, it is questionable how this approach will scale as the number of processors increases further. To address this issue, we analyze real-world rendering workloads, derive requirements for e ective pa erns, and present ten di erent pa ern design strategies based on these requirements. In addition to a theoretical evaluation of these design strategies, we compare the performance of select pa erns in a parallel sort-middle so ware rendering pipeline on an extensive set of triangle data captured from eight recent video games. As a result, we are able to identify a set of pa erns that scale well and exhibit signi cantly improved performance over na¨ıve approaches.en_US
dc.publisherACMen_US
dc.subjectComputing methodologies Rasterization
dc.subjectMassively parallel algorithms
dc.subjectStatic load balancing
dc.subjectPa ern
dc.subjectParallel Rendering
dc.subjectSort
dc.subjectmiddle
dc.subjectGPU
dc.titleEffective Static Bin Patterns for Sort-Middle Renderingen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on High Performance Graphics
dc.description.sectionheadersSpecialized Hardware Architectures
dc.identifier.doi10.1145/3105762.3105777


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