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Computation on programmable graphics hardware

机译:可编程图形硬件上的计算

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摘要

GPUs have evolved into powerful and flexible streaming processors with fully programmable floating-point pipelines and tremendous aggregate computational power and memory bandwidth. With these advances, modern GPUs can now perform more functions than the specific graphics computations for which they were designed. This article describes approaches to using GPU processing power to accelerate traditionally CPU-based tasks. We discuss some important characteristics of algorithms that make them good candidates for GPU acceleration. We discuss a specific GPU image-processing application that is a common postprocess for many physically based rendering systems.
机译:GPU已经发展成为功能强大且灵活的流处理器,具有完全可编程的浮点流水线以及巨大的聚合计算能力和内存带宽。有了这些进步,现代GPU现在可以执行比为其设计的特定图形计算更多的功能。本文介绍了使用GPU处理能力来加速传统上基于CPU的任务的方法。我们讨论了使算法成为GPU加速的良好候选者的算法的一些重要特征。我们讨论了特定的GPU图像处理应用程序,它是许多基于物理的渲染系统的常见后处理程序。

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