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OpenVX与三维渲染在多态GPU上的并行实现
引用本文:延酉玫,李涛,王鹏博,韩俊刚,李雪丹,姚静,乔虹.OpenVX与三维渲染在多态GPU上的并行实现[J].计算机应用,2015,35(1):53-57.
作者姓名:延酉玫  李涛  王鹏博  韩俊刚  李雪丹  姚静  乔虹
作者单位:1. 西安邮电大学 计算机学院, 西安710121; 2. 西安邮电大学 电子工程学院, 西安710121
基金项目:国家自然科学基金重点项目(61136002)
摘    要:针对图像处理与机器视觉以及三维图形渲染等所具有的大规模并行处理特征,通过充分利用面向图形图像处理的多态阵列架构(PAAG)处理器的可编程性以及灵活的并行处理方式,采用操作级并行与数据级并行相结合的并行化设计方法,实现了OpenVX中Kernel函数以及3D图形渲染.实验结果表明,在OpenVX标准图像处理Kernel函数以及图形渲染的并行实现中,采用PAAG处理器中的多指令多数据(MIMD)并行处理方式可以获得斜率为1的线性加速比,比传统图形处理器(GPU)中单指令多数据(SIMD)并行处理方式所得到的斜率值小于1的非线性加速比效率更高.

关 键 词:多态阵列机  仿真  OpenVX  操作并行  数据并行  
收稿时间:2014-07-23
修稿时间:2014-09-17

Parallel implementation of OpenVX and 3D rendering on polymorphic graphics processing unit
YAN Youmei;LI Tao;WANG Pengbo;HAN Jungang;LI Xuedan;YAO Jing;QIAO Hong.Parallel implementation of OpenVX and 3D rendering on polymorphic graphics processing unit[J].journal of Computer Applications,2015,35(1):53-57.
Authors:YAN Youmei;LI Tao;WANG Pengbo;HAN Jungang;LI Xuedan;YAO Jing;QIAO Hong
Affiliation:1. School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an Shaanxi 710121, China;
2. School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an Shaanxi 710121, China
Abstract:For the image processing, computer vision and 3D rendering have the feature of massive parallel processing, the programmability and the flexible mode of parallel processing on the Polymorphic Array Architecture for Graphics (PAAG) platform were utilized adequately, the parallelism design method by combing the operation level parallelism with data level parallelism was used to implement the OpenVX Kernel functions and 3D rendering pipelines. The experimental results indicate that in the parallel implementation of image processing of OpenVX Kernel functions and graphics rendering, using Multiple Instruction Multiple Data (MIMD) of PAAG in parallel processing can obtain a linear speedup that the slope equals to 1, which achieves higher efficiency than the slope as nonlinear speedup that less than 1 of Single Instruction Multiple Data (SIMD) in traditional parallel processing of the Graphics Processing Unit (GPU).
Keywords:polymorphic array processor                                                                                                                        simulation                                                                                                                        OpenVX                                                                                                                        operation parallelism                                                                                                                        data parallelism
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