| 基于GPU的数学形态学运算并行加速研究 |
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| 引用本文： | 张聪,邢同举,罗颖,张静,孙强. 基于GPU的数学形态学运算并行加速研究[J]. 电子设计工程, 2011, 19(19): 141-143,146 |
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| 作者姓名： | 张聪 邢同举 罗颖 张静 孙强 |
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| 作者单位： | 电子科技大学光电信息学院,四川成都,610054 |
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| 摘 要： | 数学形态学运算是一种高度并行的运算,其计算量大而又如此广泛地应用于对实时性要求较高的诸多重要领域。为了提高数学形态学运算的速度,提出了一种基于CUDA架构的GPU并行数学形态学运算。文章详细描述了GPU硬件架构和CUDA编程模型,并给出了GPU腐蚀并行运算的详细实现过程以及编程过程中为充分利用GPU资源所需要注意的具体问题。实验结果表明,GPU并行数学形态学运算速度可达到几个数量级的提高。
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| 关 键 词： | 数学形态学 腐蚀 GPU CUDA 加速比 |
Parallel accelerating research about mathematical morphology based on GPU |
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| ZHANG Cong,XING Tong-ju,LUO Ying,ZHANG Jing,SUN Qiang. Parallel accelerating research about mathematical morphology based on GPU[J]. Electronic Design Engineering, 2011, 19(19): 141-143,146 |
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| Authors: | ZHANG Cong XING Tong-ju LUO Ying ZHANG Jing SUN Qiang |
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| Affiliation: | (School of Opto-Electronic Information,University of Electronic Science and Technology of China, Chengdu 610054,China) |
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| Abstract: | Mathematical morphology operation is a highly parallel processing, it involves a large amount of computation and is widely used for so many important filed that have high requirements on real-time. In order to improve the speed of mathematical morphological operations, a GPU Parallel mathematical morphology operations based on CUDA is proposed in this paper. We have made a description of the GPU hardware architecture and the CUDA programming model. The specific GPU parallel implementation process of erosion operation and some problems that involves make full use of GPU resources are given in this paper too. Experimental results show that, GPU parallel computing mathematical morphology is several orders of magnitude faster than normal morphology operation. |
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| Keywords: | mathematical morphology erosion GPU CUDA speedup |
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