CPU/GPU 异构环境下图像协同并行处理模型

随着GPU通用计算能力的不断发展,一些新的更高效的处理技术应用到图像处理领域.目前已有一些图像处理算法移植到GPU中且取得了不错的加速效果,但这些算法没有充分利用CPU/GPU组成的异构系统中各处理单元的计算能力.文章在研究GPU编程模型和并行算法设计的基础上,提出了CPU/GPU异构环境下图像协同并行处理模型.该模型充分考虑异构系统中各处理单元的计算能力,通过图像中值滤波算法,验证了CPU/GPU环境下协同并行处理模型在高分辨率灰度图像处理中的有效性.实验结果表明,该模型在CPU/GPU异构环境下通用性较好,容易扩展到其他图像处理算法.

Image Cooperative Parallel Processing Model in CPU / GPU Heterogeneous Environment

In recent years, with the continuous development of GPU general computing power, more efficient processing technologies have been for image processing. At present, some image processing algorithms have been transplanted to GPU and have good effect in acceleration. However these algorithms do not make full use of the computing power of each processing unit in a hybrid systems composed by CPU/GPU. Based on GPU programming model and parallel algorithm design, we proposed image collaborative parallel processing model at CPU/GPU heterogeneous environment in this paper. The effectiveness of this model in high resolution grayscale image processing was verified by the image median filtering algorithm, which was based on the computing power of each processing unit in heterogeneous system. The experimental results show that the model performs well in CPU/GPU heterogeneous environment and is easy to execute other image processing algorithms.