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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 7
2049-2053

GPU collaborative computing model for complex applications in large-scale data processing

Zhang Longxiang1,2
Cao Yunpeng1,2
Wang Haifeng1,2
1. Information Science & Engineering School, LinYi University, Linyi Shandong 276002, China
2. Linda Institute, Shandong Provincial Key Laboratory of Network based Intelligent Computing, Linyi Shandong 276002, China
DOI: 10.19734/j.issn.1001-3695.2019.02.0016

Abstract

The large-scale data computig process includes different modes which are streaming computing, memory computing, batching computing and graph computing mode. Each mode has different access memory, communication and resource utilization. GPU clusters are widely used in large-scale data processing. However, there is lack of computing model for GPU cluster in large-scale data process. The collaborative computing between GPU and CPU not only increases density of computing resources but also improves communication complexity between inter-nodes and intra-nodes. To explore rule of collaborative computing process, this paper built a novel multi-stage collaborative computing model(p-DCOT) for multi-computing modes. This model was based on BSP model, which was large synchronous parallel model. It divided the collaborative computing process into three levels: data layer, computing layer and communication layer. This model also used matrix of DOT model to describe computing and communication behaviors. Then it extended the p-DOT model to describe collaborative computing behavior within computing nodes and refined the parameters of workloads balancie. This model could prove the time cost function of collaborative computing model. Finally, the typical computing tasks verified the model validity and parameter analysis. This collaborative computing model will be a tool to reveal collaborative computing behaviors in large-scale data analysis processing.

Foundation Support

山东省自然科学基金面上项目(ZR2017MF050)
山东省高等学校科学技术计划项目(J17KA049)
山东省重点研发项目(2018GGX101005,2017CXGC0701,2016GGX109001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.02.0016
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 7
Section: Algorithm Research & Explore
Pages: 2049-2053
Serial Number: 1001-3695(2020)07-026-2049-05

Publish History

[2020-07-05] Printed Article

Cite This Article

张龙翔, 曹云鹏, 王海峰. 面向大数据复杂应用的GPU协同计算模型 [J]. 计算机应用研究, 2020, 37 (7): 2049-2053. (Zhang Longxiang, Cao Yunpeng, Wang Haifeng. GPU collaborative computing model for complex applications in large-scale data processing [J]. Application Research of Computers, 2020, 37 (7): 2049-2053. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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