数据与计算发展前沿 ›› 2019, Vol. 1 ›› Issue (1): 35-45.

doi: 10.11871/jfdc.issn.2096.742X.2019.01.005

所属专题： “数据与计算平台”专刊

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应用驱动的大数据与人工智能融合平台建设

康波1,2,夏梓峻2,孟祥飞2   

  1. 1. 天津大学智能与计算学部,天津 300350
    2. 国家超级计算天津中心,天津 300457
  • 收稿日期:2019-08-25 出版日期:2019-01-20 发布日期:2019-10-09
  • 作者简介:康波,1986年生,博士,国家超级计算天津中心高级工程师,目前主要开展不同体系结构下大规模深度学习并行实现、人工智能可视化交互建模训练、典型场景算法开发与应用等研究。
    本文中负责融合平台框架设计、应用分析。
    Kang Bo, born in 1986, male, Ph.D., senior engineer of the National Supercomputing Tianjin Center, is currently conducting research on parallel implementation of large-scale deep learning under different architectures, interactive modeling training of artificial intelligence, and industrial-based AI development and application.
    In this paper, he is responsible for the design and application analysis of the fusion platform.
    E-mail: kangbo@nscc-tj.cn|夏梓峻,1986年生,硕士,国家超级计算天津中心应用研发部副部长,主要研究方向为高性能计算应用研发、大规模并行计算研发与优化、高性能应用软件研发、数据分析与处理、深度学习应用研发、企业智能应用场景解决方案。
    本文中负责融合环境方法介绍和应用分析。
    Xia Zijun, born in 1986, male, deputy director of Research & Application Department,National Supercomputer Center in Tianjin. His main research field contains HPC application R&D, massively parallel computing R&D, data Analysis, deep learning and industrial application solution.
    In this paper, he is responsible for writing the introduction and application analysis of the integrated environmental approach.
    E-mail: xiazj@nscc-tj.cn|孟祥飞,1979年生,理学博士,国家超级计算天津中心教授级高级工程师,主任助理,应用研发部部长,中华人民共和国国家发展和改革委员会“大数据处理技术与应用”国家地方联合实验室主任工程师;中国计算机学会高性能计算专家委员会常委,中国医促会医学数据与医学计量分会副主委,中国抗癌协会肿瘤人工智能委员会副主任委员。主要研究方向为大规模并行处理技术、大数据技术研发与应用等。
    本文中完成了论文的国内外现状分析、方法原理和结论展望。
    Meng Xiangfei, born in 1979, male, Ph.D., professor-level senior engineer, assistant director of the National Supercomputing Tianjin Center, lead of application research and development department, director of "Big Data Processing Technology and Application" National and Local Joint Laboratory, Member of the Standing Committee of the CCF High Performance Computing Expert Committee, Vice Chairman of the Medical Data and Medical Measurement Branch of the China Association for the Promotion of Medical Sciences, and Deputy Director of the Cancer Artificial Intelligence Committee of the China Anti-Cancer Association (CACA). His main research focuses on large-scale. parallel processing technology, big data technology R&D and application.
    In this paper, he is responsible for completing the analysis of both domestic and foreign research review, method principle and conclusion.
    E-mail: mengxf@nscc-tj.cn.
  • 基金资助:
    国家重点研发计划(2016YFB0201500);天津市企业博士后创新项目择优资助计划资助项目(TJQYBSH2018002)

Application-driven Big Data and Artificial Intelligence Integration Platform Construction

Bo Kang1,2,Zijun Xia2,Xiangfei Meng2   

  1. 1. College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
    2. National Supercomputer Center in Tianjin, Tianjin 300457, China
  • Received:2019-08-25 Online:2019-01-20 Published:2019-10-09

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摘要：

【目的】介绍了面向产业需求的大数据与人工智能融合平台建设思路,形成了推动传统产业智能化、智能科技产业化的发展实施方案,为计算创新驱动提供参考。【方法】基于面向行业应用场景的数据特征理解和融合平台需求分析,阐述了基于应用驱动的超级计算与大数据、云计算、人工智能、物联网融合的平台层次结构,在基础融合环境、数据整合框架、业务系统几个方面系统介绍了该融合平台的体系架构和实现。【结果】基于该平台,实现了在装备制造、网联汽车、医疗健康等领域的典型应用,具备较好的适用性。【局限】作为公共开源开放平台提供服务,机构公信力、数据安全性是其下一步需要解决的重要问题。【结论】应用驱动的大数据与人工智能融合平台可作为社会开发、政府可控的智能产业科学发展生态的重要组成部分,进一步解决我国智能产业领域创新能力和创新支撑平台不足的现实问题。

关键词: 超级计算, 大数据, 人工智能, 融合平台

Abstract:

[Objective]In order to provide references for computational innovations, an industrial needs driven integration platform for big data and artificial intelligence analysis and application is proposed to promote the traditional industry intelligence and intelligent technology industrialization. [Methods]Based on the integration of both data feature understanding and platform requirements in industry-oriented application scenarios, the application-driven platform hierarchy in supercomputer center is designed in a fused architecture consists of supercomputing, big data, cloud computing, artificial intelligence and internet of things, which contains implications on physical facilities, system software and management system. In the supercomputer center, it mainly integrates service-related hardware facilities for big data, super-computing and cloud computing to realize data sharing, high-performance processing, and data security control. By eliminating the difference between various data sources, the platform provides an unified standard data access interface for upper-layer applications, which promotes standardization of big data processing in related industries for resource and data sharing. As an important field of big data applications, the high-efficiency big data application platform for industrials combines with the industrial cloud platform to realize data collection, transmission, collaboration and application by integrating the physical device, virtual network and big data analysis methods. The characteristics of industrial-based big data and artificial intelligence require innovative applications that support the production tasks, such as design, production, sales, operation and maintenance. [Results]Based on the platform, it has achieved typical applications in industrial fields such as equipment manufacturing, networked vehicles, medical health, etc., showing good applicability. In manufacturing, the platform is a tool for product supplier quality management control, carrying out abnormal inspection and prediction of parts and components, and achieving management ability to control the entire product chain. In networked vehicle, by collecting vehicle driving data and using deep learning modeling, it is possible to analyze the safety of autonomous driving and driving behavior. In disease screening, big data and artificial intelligence analysis for radiological imaging, pathology images, and electronic medical records can help doctors complete analysis of repetitive tasks and complex tasks. [Limitations]As a public open platform to provide services, institutional credibility and data security are important issue to be solved in the next step. [Conclusions]Application-driven big data and artificial intelligence integration platform acts as an important part of social development and government-controllable intelligent industry science development ecology, which further solves the practical problems that insufficient innovation ability in China's intelligent industry.

Key words: supercomputing, big data, artificial intelligence, fusion platform on big data and AI