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Cache-friendly micro-jittered sampling

Arthur Dufay 1, 2, 3 Pascal Lecocq 2 Romain Pacanowski 3, 1 Jean-Eudes Marvie 2 Xavier Granier 3, 1 
1 MANAO - Melting the frontiers between Light, Shape and Matter
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, LP2N - Laboratoire Photonique, Numérique et Nanosciences
Abstract : Monte-Carlo integration techniques for global illumination are popular on GPUs thanks to their massive parallel architecture, but efficient implementation remains challenging. The use of randomly de-correlated low-discrepancy sequences in the path-tracing algorithm allows faster visual convergence. However, the parallel tracing of incoherent rays often results in poor memory cache utilization, reducing the ray bandwidth efficiency. Interleaved sampling [Keller et al. 2001] partially solves this problem, by using a small set of distributions split in coherent ray-tracing passes, but the solution is prone to structured noise. On the other hand, ray-reordering methods [Pharr et al. 1997] group stochastic rays into coherent ray packets but their implementation add an additional sorting cost on the GPU [Moon et al. 2010] [Garanzha and Loop 2010]. We introduce a micro-jittering technique for faster multi-dimensional Monte-Carlo integration in ray-based rendering engines. Our method, improves ray coherency between GPU threads using a slightly altered low-discrepancy sequence rather than using ray-reordering methods. Compatible with any low-discrepancy sequence and independent of the importance sampling strategy, our method achieves comparable visual quality with classic de-correlation methods, like Cranley-Patterson rotation [Kollig and Keller 2002], while reducing rendering times in all scenarios.
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Submitted on : Thursday, June 2, 2016 - 3:37:50 PM
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Arthur Dufay, Pascal Lecocq, Romain Pacanowski, Jean-Eudes Marvie, Xavier Granier. Cache-friendly micro-jittered sampling. SIGGRAPH 2016, Jul 2016, Anaheim, United States. ⟨10.1145/2897839.2927392⟩. ⟨hal-01325702⟩



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