数据与计算发展前沿 ›› 2019, Vol. 1 ›› Issue (1): 46-62.doi: 10.11871/jfdc.issn.2096.742X.2019.01.006

所属专题: “数据与计算平台”专刊

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面向大规模数据的科学可视化系统GPVis

单桂华1,*(),刘俊1,2,李观1,2,高阳1,徐涛1,田东1,2   

  1. 1.中国科学院计算机网络信息中心,北京 100190
    2.中国科学院大学,北京 100049
  • 收稿日期:2019-08-15 出版日期:2019-01-20 发布日期:2019-10-09
  • 通讯作者: 单桂华
  • 作者简介:单桂华,1976年生,中国科学院计算机网络信息中心,研究员,主要研究方向为可视化与可视分析、智能交互。
    本文承担工作为: GPVis整体架构设计、研究指导。
    Shan Guihua, born in 1976,Computer Network Information Center of the Chinese Academy of Sciences, research fellow. Her main research interests are visualization, visual analysis and intelligent interaction.
    In this paper she undertakes the following tasks: the overall structure design and research guidance of the framework.E-mail:sgh@cnic.cn|刘俊,1982年生,中国科学院计算机网络信息中心,高级工程师,主要研究方向为科学数据可视化及可视分析。
    本文承担工作为:任务及需求分析、软件框架实现、核心算法研究与实现。
    Liu Jun, born in 1982, Computer Network Information Center of the Chinese Academy of Sciences, senior engineer. His main research interests are scientific data visualization and visual analysis.
    In this paper he undertakes the following tasks: task and demand analysis, software framework implementation and key algorithms research as well as their implementation.E-mail: liujun@sccas.cn|李观,1990年生,中国科学院计算机网络信息中心,博士研究生,主要研究方向为科学可视化与可视分析。
    本文承担工作为:粒子可视化研究与实现、多终端协同组件设计与开发、可视化应用研发。
    Li Guan, born in 1990, Computer Network Information Center of Chinese Academy of Sciences,PhD student. His main research interests are scientific visualization and visual analysis.
    In this paper he undertakes the following tasks: visualization, design and implementation of particle data, cooperative component development design and visualization application implementation.E-mail: liguan@sccas.cn|高阳,1987年生,中国科学院计算机网络信息中心,工程师,主要研究方向为科学可视化与可视分析。
    本文承担工作为:可视化组件开发与测试、可视化应用开发。
    Gao Yang, born in 1987, Computer Network Information Center of Chinese Academy of Sciences, engineer. Her main research interests are scientific visualization and visual analysis.
    In this paper she undertakes the following tasks: visualization component development and test, visualization application implementation.E-mail: gaoyang@cnic.cn|徐涛,1992年生,中国科学院计算机网络信息中心,助理工程师,主要研究方向为科学数据可视化、先进渲染技术。
    本文承担工作为:可视化组件设计开发, 可视化应用开发。
    Xu Tao, born in 1992, Computer Network Information Center of the Chinese Academy of Sciences, assistant engineer. His main research interests are scientific data visualization and photorealistic rendering.
    In this paper he undertakes the following tasks: visualization component design and development, domain visualization application implementation.E-mail: xutao@cnic.cn|田东,1983年生,中国科学院计算机网络信息中心,高级工程师,主要研究方向为数据可视化及可视分析。
    本文承担工作为:核心算法研究与实现。
    Tian Dong, born in 1983, Computer Network Information Center of Chinese Academy of Sciences, senior engineer. His main research interests are data visualization and visual analysis.
    In this paper he undertakes the following tasks: key algorithms research and implementation.E-mail: tiandong@cnic.cn
  • 基金资助:
    中国科学院信息化专项(XXH13503-07);中国科学院信息化专项(XXH13506-402)

GPVis: A Scientific Visualization System for Large Scale Data

Guihua Shan1,*(),Jun Liu1,2,Guan Li1,2,Yang Gao1,Tao Xu1,Dong Tian1,2   

  1. 1.Chinese Academy of Sciences, Computer Network Information Center, Beijing 100190, China
    2.University of Chinese Academy of Sciences, Beijing 100190, China
  • Received:2019-08-15 Online:2019-01-20 Published:2019-10-09
  • Contact: Guihua Shan

摘要:

【目的】为解决大规模科学数据可视化所面临的一系列问题,提供一套灵活可扩展的科学数据可视化框架,本文设计并实现一种面向大规模数据的科学可视化系统GPVis。【方法】本文基于科学数据可视化在方法和工具层面所面临的挑战和机遇进行了分析,结合数据预组织、图形渲染、高性能计算、人机交互、VR/AR等相关的先进技术,提出了新型的可视化计算及服务框架。【结果】针对常用的可视化方法,本文提出了适用于GPVis框架的可视化处理模式,并列举了多个该可视化框架系统在典型领域的应用案例的具体方法及结果,实现并满足了科学研究人员在数据分析中的可视化需求。【局限】GPVis在智能分析方面还有待进一步提升,未来将与人工智能技术更紧密结合。【结论】GPVis提供了强大且可扩展的大规模科学数据可视化的平台框架,可以针对不同的数据类型及应用需求进行灵活的组件设计,随着系统在框架结构及可视化算法上的不断发展完善,将在更多的科学领域得到应用。

关键词: 科学可视化, 大规模科学数据, 软件系统, 大科学装置, 虚拟现实

Abstract:

[Objective]To solve a series of problems brought about by large-scale scientific data visualization, and to provide a flexible and scalable scientific data visualization framework, this paper proposes GPVis, a scientific visualization system for large-scale data. [Methods]In this paper, we analyzed the challenges and opportunities faced by scientific data visualization at both the method and tool level. A new visual computing and service framework, GPVis, is proposed by using advanced technologies such as data pre-organization, graphics rendering, high-performance computing, human-computer interaction, VR/AR, etc.. [Results]For some common visualization methods, this paper proposes several visualization processing models for GPVis framework, and enumerates several application cases of the system in typical fields with provided specific implementation methods and results. In these cases, different types of visualization need of scientific researchers for data analysis were met. [Limitations]GPVis needs more intelligence for data analysis which leads us to incorporate artificial intelligence technology into future developments and introduce more natural human-computer interaction methods. [Conclusions]GPVis provides a powerful and scalable platform framework for large-scale scientific data visualization, enabling flexible component design for different data types and application requirements. As the system continues to evolve by providing more complete framework functions and visualization algorithms, it will be applied to more scientific fields in the future.

Key words: scientific visualization, large scale scientific data, software system, Mega Science Facilities, virtual reality