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CUDAGA: A Portable Parallel Programming Model for GPU Cluster

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Cloud Computing and Big Data (CloudCom-Asia 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9106))

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Abstract

GPU cluster is important for high performance computing with its high performance/cost ratio. However, it is still very hard for application developers to write parallel codes on GPU. MPI is mostly used for parallel programming, and data locality and communication must be specified explicitly by developers. Moreover, data transmission between CPU and GPU must also be processed with CUDA codes. CUDAGA, a new parallel programming model for GPU cluster with CUDA, is presented to provide portable interfaces for commu-nication on GPUs. GA (Global Arrays), a portable shared-memory programming model for distributed memory computers, is the base to facilitate parallel pro-gramming and maintain transparent global arrays on GPUs. Experiments show that CUDAGA can decrease parallel programming difficulties, but ensures better performance for some specific applications.

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Acknowledgment

This work is supported by the National 973 Key Basic Research Plan of China (No. 2013CB2282036), the Major Subject of the State Grid Corporation of China (No. SGCC-MPLG001(001-031)-2012), the National 863 Basic Research Program of China (No. 2011AA05A118), the National Natural Science Foundation of China (No. 61133008), the National Science and Technology Pillar Program (No. 2012BAH14F02) and the independent innovation project of Huazhong University of Science and Technology.

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Authors and Affiliations

  1. Services Computing Technology and System Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Yong Chen, Hai Jin, Ran Zheng, Haocheng Liu & Jingxiang Zeng

  2. China Electric Power Research Institute, Beijing, 100192, China

    Yong Chen & Dechao Xu

Authors
  1. Yong Chen
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  2. Hai Jin
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  3. Dechao Xu
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  4. Ran Zheng
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  5. Haocheng Liu
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  6. Jingxiang Zeng
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Corresponding author

Correspondence to Ran Zheng .

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Editors and Affiliations

  1. School of Computer Science and Tech., Huazhong Univ. of Science and Technology, Wuhan, China

    Weizhong Qiang

  2. College of Mathematics and Computer Sci., Fuzhou University, Fuzhou, China

    Xianghan Zheng

  3. Dept. of Computer Scie and Informat. Eng, Chung Hua University, Hsinchu, Taiwan

    Ching-Hsien Hsu

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© 2015 Springer International Publishing Switzerland

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Chen, Y., Jin, H., Xu, D., Zheng, R., Liu, H., Zeng, J. (2015). CUDAGA: A Portable Parallel Programming Model for GPU Cluster. In: Qiang, W., Zheng, X., Hsu, CH. (eds) Cloud Computing and Big Data. CloudCom-Asia 2015. Lecture Notes in Computer Science(), vol 9106. Springer, Cham. https://doi.org/10.1007/978-3-319-28430-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-28430-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28429-3

  • Online ISBN: 978-3-319-28430-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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