Rendering complex scenes with memory-coherent ray tracing
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Interactive multi-pass programmable shading
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
An improved illumination model for shaded display
Communications of the ACM
Ray tracing on programmable graphics hardware
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Efficient partitioning of fragment shaders for multipass rendering on programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Using modern graphics architectures for general-purpose computing: a framework and analysis
Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture
Simulation of cloud dynamics on graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Linear algebra operators for GPU implementation of numerical algorithms
ACM SIGGRAPH 2003 Papers
Radiosity on graphics hardware
GI '04 Proceedings of the 2004 Graphics Interface Conference
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
KD-tree acceleration structures for a GPU raytracer
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
GPGPU: general purpose computation on graphics hardware
ACM SIGGRAPH 2004 Course Notes
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Today's hardware includes powerful devices such as graphics process units (GPU) that are not always used to their maximum capacities. Our main goal is to take advantage of these unused resources. To achieve this, we abstract GPUs as SIMD streaming coprocessors and use them within the framework of a multithreaded parallel model. Thus we aim to use all the computing power of a modern PC for speeding up a global illumination simulation software. The global illumination of a virtual scene can be estimated with stochastic methods such as Path Tracing. These methods however remain costly in terms of rendering time, because of the high sampling required to produce good quality frames. The most part of the rendering time is spent performing intersections tests between rays and triangles. We propose to speed up the rendering of a frame, by using all the available CPUs and GPUs. Our work is based on the ray engine developed by Carr et al. for ray tracing, and is mapped to our parallel programming model.