并行算法,并行设计范式,图像处理,多核计算环境,可扩展性," /> 并行算法,并行设计范式,图像处理,多核计算环境,可扩展性,"/> 多核图像处理并行设计范式的研究与应用

计算机工程 ›› 2011, Vol. 37 ›› Issue (14): 220-222.doi: 10.3969/j.issn.1000-3428.2011.14.074

• 图形图像处理 • 上一篇    下一篇

多核图像处理并行设计范式的研究与应用

王成良 a,谢克家 b,刘 昕 a   

  1. (重庆大学 a. 软件工程学院;b. 计算机学院,重庆 400044)
  • 收稿日期:2011-01-05 出版日期:2011-07-20 发布日期:2011-07-20
  • 作者简介:王成良(1964-),男,教授、博士,主研方向:并行分布式计算,图形与图像处理,数据库技术;谢克家,硕士研究生;刘 昕,本科生
  • 基金项目:

    重庆市科技攻关计划基金资助项目(CSTC, 2009AC2060)

Research and Application of Multi-core Image Processing Parallel Design Scheme

WANG Cheng-liang a, XIE Ke-jia b, LIU Xin a   

  1. (a. School of Software Engineering; b. College of Computer Science, Chongqing University, Chongqing 400044, China)
  • Received:2011-01-05 Online:2011-07-20 Published:2011-07-20

摘要:

多核计算环境下采用图像处理并行算法可提高图像处理的速度,但已有的并行设计只针对边缘检测、图像投影等特定算法进行,没有形成通用的并行算法设计范式。为此,在研究图像处理算法可并行处理机制和多核架构特点的基础上,提出分析、建模、映射、调试和性能评价及测试发布等5个设计步骤的基于多核计算环境的图像处理算法并行设计范式,以图像傅里叶变换并行算法设计为例在单核、双核、四核、八核计算环境下验证了该并行范式的有效性。实验结果表明,该范式在图像处理并行设计方面可扩展图像处理的应用空间。

关键词:

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Abstract:

In multi-core computing environment, the image processing parallel algorithms can greatly improve the processing speed. However,the existing parallel designs are focused on the specific algorithms such as edge detection and image projection, which can not form a universal design scheme. Thus, it is difficult to extend this application. Based on the in-depth study of the image algorithms parallel processing mechanism and the features of the multi-core architecture, this paper proposes an image processing parallel design scheme in multi-core computing environment, which has five steps, including analysis, modeling, mapping, debugging & performance evaluation and testing & release. The paper takes the algorithm design of parallel image Fourier transforms as an example to testify the effectiveness of this scheme in single-core, double-core, quad-core and eight-core computing environment. Experimental result shows that the proposed multi-core parallel design scheme has good scalability, and this scheme can extend the space of application for image processing.

Key words: parallel algorithm, parallel design scheme, image processing, multi-core computing environment, scalability

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