Massively parallel implementations of adaptively subdividing fractal generating algorithms with parameter extensions
Fractal approximations are used to generate data to mimic natural objects for realistic image synthesis. While many algorithms for generating fractal data for this purpose exist, the adaptive subdivision methods are in widespread use because of their computational efficiency. This paper discusses the adaptation of the triangular and rectangular subdivision algorithms originally described in  to massively parallel SIMD architectures. In addition, the algorithms are enhanced to permit more control over the characteristics of the surfaces.
KeywordsStochastic Component Child Type Triangular Patch Adjacent Patch Subdivision Algorithm
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