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Section 3: Statistical Modeling - Pg. 229

SECTION Statistical Modeling Area Editor's Introduction Mike Giles 3 16 Parallelization Techniques for Random Number Generators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 17 Monte Carlo Photon Transport on the GPU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 18 High-Performance Iterated Function Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 STATE OF GPU COMPUTING IN STATISTICAL MODELING Many kinds of statistical modeling are naturally suited for GPU computing owing to their inherent parallelism. For example, in Monte Carlo simulation there are usually many independent simulations