reduction algorithm optimization based on the opencl

ISCAS OpenIR

	reduction algorithm optimization based on the opencl
	Yan Shen-Gen; Zhang Yun-Quan; Long Guo-Ping; Li Yan
	2011
发表期刊	Ruan Jian Xue Bao/Journal of Software
ISSN	1000-9825
卷号	22 期号:UPPL. 2 页码:163-171
摘要	Reduction algorithm has a wide range of applications in areas such as scientific computing and image processing. This paper systematically studies the reduction algorithm optimization on the GPU's cross-platform performance optimization based on the OpenCL framework. Previous research has generally focused on a single hardware architecture, however, this paper based on the OpenCL, studies various kinds of optimization methods, such as using vector, on-chip memory bank conflict, threads organization, instruction selection and so on. The research takes the minMax function for example, dilatationed each optimization method for develep the performance, and detailed the reason. The study tests the algorithm both on AMD GPU and NVIDIA GPU platforms. The test results show that the optimized algorithm on both platforms has achieved good performance. In the AMD ATI Radeon HD 5850 platform, Int and Float types of data bandwidth utilization up to 89%. In the NVIDIA GPU Tesla C2050 platform, the performance has reached 1.3 to 1.9 times compare to appropriate function version of CUDA. ©2011 Journal of Software.; Reduction algorithm has a wide range of applications in areas such as scientific computing and image processing. This paper systematically studies the reduction algorithm optimization on the GPU's cross-platform performance optimization based on the OpenCL framework. Previous research has generally focused on a single hardware architecture, however, this paper based on the OpenCL, studies various kinds of optimization methods, such as using vector, on-chip memory bank conflict, threads organization, instruction selection and so on. The research takes the minMax function for example, dilatationed each optimization method for develep the performance, and detailed the reason. The study tests the algorithm both on AMD GPU and NVIDIA GPU platforms. The test results show that the optimized algorithm on both platforms has achieved good performance. In the AMD ATI Radeon HD 5850 platform, Int and Float types of data bandwidth utilization up to 89%. In the NVIDIA GPU Tesla C2050 platform, the performance has reached 1.3 to 1.9 times compare to appropriate function version of CUDA. ©2011 Journal of Software.
收录类别	EI
关键词	Image Processing Optimization
部门归属	(1) Laboratory of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences Beijing 100190 China; (2) State Key Laboratory of Computing Science Institute of Software Chinese Academy of Sciences Beijing 100190 China; (3) Graduate University Chinese Academy of Sciences Beijing 100190 China
语种	中文
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16156
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Yan Shen-Gen,Zhang Yun-Quan,Long Guo-Ping,et al. reduction algorithm optimization based on the opencl[J]. Ruan Jian Xue Bao/Journal of Software,2011,22(UPPL. 2):163-171.
APA	Yan Shen-Gen,Zhang Yun-Quan,Long Guo-Ping,&Li Yan.(2011).reduction algorithm optimization based on the opencl.Ruan Jian Xue Bao/Journal of Software,22(UPPL. 2),163-171.
MLA	Yan Shen-Gen,et al."reduction algorithm optimization based on the opencl".Ruan Jian Xue Bao/Journal of Software 22.UPPL. 2(2011):163-171.