“Faster GPU Computations Using Adaptive Refinement”

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    Faster GPU Computations Using Adaptive Refinement


    We present a technique for improving the speed of multi-pass GPU computations by using adaptive refinement. We tile the screen and use occlusion queries to adaptively cull inactive parts of the computation. An implementation of this technique in a photon map renderer and a Mandelbrot fractal has resulted in speedups of up to one order of magnitude. Our technique is applicable to many of the recently developed multi-pass algorithms running on GPUs. It is easy to implement and often provides significant speedups by exploiting computational similarity, coherence, and locality.


    Bolz, J., Farmer, I., Grinspun, E., and Schröder, P. 2003. Sparse matrix solvers on the gpu: Conjugate gradients and multigrid. In Proceedings of ACM SIGGRAPH.]]
    Purcell, T. J., Donner, C., Cammarano, M., Jensen, H. W., and Hanrahan, P. 2003. Photon mapping on programmable graphics hardware. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Graphics Hardware.]]

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