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Memory-Efficient Single-Pass GPU Rendering of Multifragment Effects

机译:内存高效的多片段效果单通道GPU渲染

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Rendering multifragment effects using graphics processing units (GPUs) is attractive for high speed. However, the efficiency is seriously compromised, because ordering fragments on GPUs is not easy and the GPU's memory may not be large enough to store the whole scene geometry. Hitherto, existing methods have been unsuitable for large models or have required many passes for data transmission from CPU to GPU, resulting in a bottleneck for speedup. This paper presents a stream method for accurate rendering of multifragment effects. It decomposes the model into parts and manages these in an efficient manner, guaranteeing that the parts can easily be ordered with respect to any viewpoint, and that each part can be rendered correctly on the GPU. Thus, we can transmit the model data part by part, and once a part has been loaded onto the GPU, we immediately render it and composite its result with the results of the processed parts. In this way, we need only a single pass for data access with a very low bounded memory requirement. Moreover, we treat parts in packs for further acceleration. Results show that our method is much faster than existing methods and can easily handle large models of any size.
机译:使用图形处理单元(GPU)渲染多片段效果对于高速有吸引力。但是,效率受到严重损害,因为在GPU上排序片段并不容易,并且GPU的内存可能不足以存储整个场景几何。迄今为止,现有方法不适用于大型模型,或者需要多次通过才能将数据从CPU传输到GPU,从而导致加速瓶颈。本文提出了一种精确渲染多片段效果的流方法。它将模型分解成多个部分并以有效的方式进行管理,从而确保可以轻松地针对任何视点对这些部分进行排序,并且可以在GPU上正确渲染每个部分。因此,我们可以逐部分传输模型数据,将零件数据加载到GPU后,我们立即对其进行渲染,并将其结果与已处理零件的结果进行合成。这样,我们只需要一次访问就可以访问具有非常低的有限内存需求的数据。此外,我们将包装中的零件进行处理以进一步加速。结果表明,我们的方法比现有方法快得多,并且可以轻松处理任何大小的大型模型。

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