Institute of Computing Technology, Chinese Academy IR
A multi-GPU parallel optimization model for the preconditioned conjugate gradient algorithm | |
Gao, Jiaquan1,4; Zhou, Yuanshen2; He, Guixia3; Xia, Yifei1 | |
2017-04-01 | |
发表期刊 | PARALLEL COMPUTING |
ISSN | 0167-8191 |
卷号 | 63页码:1-16 |
摘要 | In this study, we present a novel optimization model that can automatically and rapidly generate an optimally parallel preconditioned conjugate gradient (PCG) algorithm for any given linear system on a specific multi-graphics processing unit (GPU) platform. For our proposed model, there are the following novelties: (1) a profile-based performance model for each one of the main components of the PCG algorithm, including the vector operation, inner product, and sparse matrix-vector multiplication (SpMV), is suggested, and (2) our model is general, independent of the problems, and only dependent on the resources of devices, and (3) our model is extensible. For a vector operation kernel, or inner product kernel, or SpMV kernel that is not included in our framework, once its performance model is successfully constructed, it can be incorporated into our framework. Our model is constructed only once for each type of GPU. The experiments validate the high efficiency of our proposed model. (C) 2017 Elsevier B.V. All rights reserved. |
关键词 | Optimization model Preconditioned conjugate gradient algorithm CUDA Multiple GPUs |
DOI | 10.1016/j.parco.2017.04.003 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Natural Science Foundation of Zhejiang Province, China[LY17F020021] ; Open Project Program of the State Key Laboratory of Computer Architecture[CARCH201603] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Theory & Methods |
WOS记录号 | WOS:000401212100001 |
出版者 | ELSEVIER SCIENCE BV |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/7183 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Gao, Jiaquan |
作者单位 | 1.Nanjing Normal Univ, Sch Comp Sci & Technol, Nanjing 210023, Jiangsu, Peoples R China 2.Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China 3.Zhejiang Univ Technol, Zhijiang Coll, Hangzhou 310024, Zhejiang, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Gao, Jiaquan,Zhou, Yuanshen,He, Guixia,et al. A multi-GPU parallel optimization model for the preconditioned conjugate gradient algorithm[J]. PARALLEL COMPUTING,2017,63:1-16. |
APA | Gao, Jiaquan,Zhou, Yuanshen,He, Guixia,&Xia, Yifei.(2017).A multi-GPU parallel optimization model for the preconditioned conjugate gradient algorithm.PARALLEL COMPUTING,63,1-16. |
MLA | Gao, Jiaquan,et al."A multi-GPU parallel optimization model for the preconditioned conjugate gradient algorithm".PARALLEL COMPUTING 63(2017):1-16. |
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