Active Thread Compaction for GPU Path Tracing

dc.contributor.authorWald, Ingoen_US
dc.contributor.editorCarsten Dachsbacher and William Mark and Jacopo Pantaleonien_US
dc.date.accessioned2016-02-18T11:01:48Z
dc.date.available2016-02-18T11:01:48Z
dc.date.issued2011en_US
dc.description.abstractModern GPUs like NVidia s Fermi internally operate in a SIMD manner by ganging multiple (32) scalar threads together into SIMD warps; if a warp s threads diverge, the warp serially executes both branches, temporarily disabling threads that are not on that path. In this paper, we explore and thoroughly analyze the concept of active thread compaction i.e., the process of taking multiple partially-filled warps and compacting them to fewer but fully utilized warps in the context of a CUDA path tracer. Our results show that this technique can indeed lead to significant improvements in SIMD utilization, and corresponding savings in theamount of work performed; however, they also show that certain inadequacies of today s hardware wipe out most of the achieved gains, leaving bottom-up speed-ups of a mere 12 16%. We believe our analysis of why this is the case will provide insight to otherresearchers experimenting with this technique in different contexts.en_US
dc.description.sectionheadersParallel Ray Tracingen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on High Performance Graphicsen_US
dc.identifier.doi10.1145/2018323.2018331en_US
dc.identifier.isbn978-1-4503-0896-0en_US
dc.identifier.issn2079-8687en_US
dc.identifier.pages51-58en_US
dc.identifier.urihttps://doi.org/10.1145/2018323.2018331en_US
dc.publisherACMen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree DimensionalGraphics and Realism Raytracingen_US
dc.titleActive Thread Compaction for GPU Path Tracingen_US
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