Memory bandwidth optimization of SpMV on GPGPUs

doi:10.1007/s11704-014-4127-1

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Memory bandwidth optimization of SpMV on GPGPUs
	Yan, Chenggang Clarence 1,2; Yu, Hui 2; Xu, Weizhi 3,4; Zhang, Yingping 5; Chen, Bochuan 5; Tian, Zhu 6; Wang, Yuxuan 6; Yin, Jian 6
刊名	FRONTIERS OF COMPUTER SCIENCE
	2015-06-01
卷号	9 期号:3 页码:431-441
关键词	GPGPU performance tuning SpMV cache blocking memory bandwidth
ISSN号	2095-2228
DOI	10.1007/s11704-014-4127-1
英文摘要	It is an important task to improve performance for sparse matrix vector multiplication (SpMV), and it is a difficult task because of its irregular memory access. General purpose GPU (GPGPU) provides high computing ability and substantial bandwidth that cannot be fully exploited by SpMV due to its irregularity. In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to exploit memory bandwidth of GPU architecture more efficiently. The new storage format can ensure that there are as many non-zeros as possible in the format which is suitable to exploit the memory bandwidth of the GPU. Second, we propose a cache blocking method to improve the performance of SpMV on GPU architecture. The sparse matrix is partitioned into sub-blocks that are stored in CSR format.With the blocking method, the corresponding part of vector x can be reused in the GPU cache, so the time to access the global memory for vector x is reduced heavily. Experiments are carried out on three GPU platforms, GeForce 9800 GX2, GeForce GTX 480, and Tesla K40. Experimental results show that both new methods can efficiently improve the utilization of GPU memory bandwidth and the performance of the GPU.
资助项目	China Major ST Project[2013ZX01033001-001-003] ; International S&T Cooperation Project of China[2012DFA11170] ; Tsinghua Indigenous Research Project[20111080997] ; National Natural Science Foundation of China[61472203] ; National Natural Science Foundation of China[61274131] ; NVIDIA Corporation
WOS研究方向	Computer Science
语种	英语
出版者	HIGHER EDUCATION PRESS
WOS记录号	WOS:000354194300009
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/9689]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xu, Weizhi
作者单位	1.Tsinghua Univ, Automat Dept, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Tsinghua Univ, Inst Microelect, Beijing 100084, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 5.State Grid Informat & Commun Co Hunan EPC, Changsha 410007, Hunan, Peoples R China 6.Shandong Univ, Dept Comp, Weihai 250101, Peoples R China
推荐引用方式 GB/T 7714	Yan, Chenggang Clarence,Yu, Hui,Xu, Weizhi,et al. Memory bandwidth optimization of SpMV on GPGPUs[J]. FRONTIERS OF COMPUTER SCIENCE,2015,9(3):431-441.
APA	Yan, Chenggang Clarence.,Yu, Hui.,Xu, Weizhi.,Zhang, Yingping.,Chen, Bochuan.,...&Yin, Jian.(2015).Memory bandwidth optimization of SpMV on GPGPUs.FRONTIERS OF COMPUTER SCIENCE,9(3),431-441.
MLA	Yan, Chenggang Clarence,et al."Memory bandwidth optimization of SpMV on GPGPUs".FRONTIERS OF COMPUTER SCIENCE 9.3(2015):431-441.