Early Visibility Resolution for Removing Ineffectual Computations in the Graphics Pipeline

Martí Anglada, Enrique de Lucas, Joan-Manuel Parcerisa, Juan L. Aragón, Antonio González
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引用次数: 7

Abstract

GPUs' main workload is real-time image rendering. These applications take a description of a (animated) scene and produce the corresponding image(s). An image is rendered by computing the colors of all its pixels. It is normal that multiple objects overlap at each pixel. Consequently, a significant amount of processing is devoted to objects that will not be visible in the final image, in spite of the widespread use of the Early Depth Test in modern GPUs, which attempts to discard computations related to occluded objects. Since animations are created by a sequence of similar images, visibility usually does not change much across consecutive frames. Based on this observation, we present Early Visibility Resolution (EVR), a mechanism that leverages the visibility information obtained in a frame to predict the visibility in the following one. Our proposal speculatively determines visibility much earlier in the pipeline than the Early Depth Test. We leverage this early visibility estimation to remove ineffectual computations at two different granularities: pixel-level and tile-level. Results show that such optimizations lead to 39% performance improvement and 43% energy savings for a set of commercial Android graphics applications running on stateof-the-art mobile GPUs.
消除图形管道中无效计算的早期可见性解决方案
gpu的主要工作是实时图像渲染。这些应用程序获取(动画)场景的描述并生成相应的图像。通过计算所有像素的颜色来渲染图像。多个对象在每个像素重叠是正常的。因此,尽管在现代gpu中广泛使用早期深度测试,但仍有大量的处理致力于在最终图像中不可见的对象,该测试试图丢弃与遮挡对象相关的计算。由于动画是由一系列相似的图像创建的,可见性通常不会在连续的帧之间发生太大变化。基于这一观察,我们提出了早期能见度分辨率(EVR),这是一种利用在一帧中获得的能见度信息来预测下一帧能见度的机制。我们的建议推测性地比早期深度测试更早地确定管道的可见性。我们利用这种早期可见性估计来消除两个不同粒度的无效计算:像素级和瓷砖级。结果表明,对于运行在最先进的移动gpu上的一组商业Android图形应用程序,这种优化导致39%的性能提升和43%的能源节约。
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