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Coherent Metropolis light transport using speculative mutations

The Metropolis Light Transport algorithm generates physically based images with superior image quality than classical ray tracing. Although it is trivially parallelizable on GPUs by running N MLTs, the performance on current graphics hardware is below par. One of the main problems is the set of incoherent paths due to the independent Markov chains. Since each MLT generates full paths and mutates them sequentially, we construct totally incoherent rays which in negatively affects the performance on the GPU. By using a novel speculative variant of the Metropolis algorithm we increase the similarity of paths and achieve higher coherence. This decreases the computation time significantly. Further, we improve memory access by optimizing the data layout to better utilize coalesced access.

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