“Faster GPU Computations Using Adaptive Refinement”
Conference:
Type:
Title:
- Faster GPU Computations Using Adaptive Refinement
Abstract:
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.
References:
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.]]
