Global Illumination aims to generate high quality images. But due to its high
requirements, it is usually quite slow. Research documented in this thesis was
intended to offer a hardware and software combined acceleration solution to
global illumination. The GPU (using CUDA) was the hardware part of the whole
method that applied parallelism to increase performance; the “Lightcuts”
algorithm proposed by Walter (2005) at SIGGRAPH 2005 acted as the software
method. As the results demonstrated in this thesis, this combined method offers
a satisfactory performance boost effect for relatively complex scenes.


GPU Global Illumination Lightcuts Performance

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