中文摘要：

在GPU上进行多片元效果的绘制,已有的方法往往需要对模型进行多遍的数据读取,以进行片元的有效排序.由于往GPU传输数据的带宽限制,多遍的数据读取严重制约了绘制效率的提高.虽然,随着CUDA的出现,已有方法可将数据完全装入GPU进行多片元效果的绘制,但受存储空间的限制,难以处理大规模的模型.对此,文中提出一种只需要单遍数据读取的绘制方法,即将模型进行凸多面体方式的组织,并依据绘制的需求逐个地将凸多面体传输到GPU中,以实现片元的正确排序.在这过程中,及时地进行同像素片元的色彩混合操作,以大幅降低片元排序的空间需求,由此可使用更多的光照参数来增强绘制效果.实验表明,新方法优化了模型的数据读取,可有效提高绘制速度,即便与基于CUDA的一次性装载数据的方法相比,也能提高速度,且能方便地处理大模型和深度层次大的模型.

英文摘要：

Rendering of multi-fragment effects can be greatly accelerated on the GPU. However, existing methods always need to read the model data in more than one passes, due to the requirements for depth ordering of fragments and the architecture limitation of the GPU. This has been a bottleneck for increasing the rendering efficiency, because of the limited transmittance band- width from CPU to GPU. Though there have been methods proposed to use CUDA with the data loaded once, they cannot process large models due to the limited storage on the GPU. This paper proposes a new method to implement single-pass GPU rendering of multi-fragment effects. It first decomposes the 3D model into a set of convex polyhedrons, and then by the viewpoint determines the order of transmitting the convex polyhedrons one by one to the GPU, to guarantee the correct ordering of fragments. In the process, the new method immediately performs illumination computation and blends the rendering results of the transmitted convex polyhedrons, so that it can greatly reduce the storage requirement. As a result, it can take more shading parameters to promote the rendering effects. Experimental results show that the new method can be faster than existing methods, even compared with the methods using CUDA, and can conveniently handle large models, even those with high depth complexity.