• DocumentCode
    2571045
  • Title

    Apply cluster and grid computing on parallel 3D rendering

  • Author

    Yang, Chao-Tung ; Lai, Chuan-Lin

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Tunghai Univ., Taichung
  • Volume
    2
  • fYear
    2004
  • fDate
    30-30 June 2004
  • Firstpage
    859
  • Abstract
    A cluster is a collection of independent and cheap machines, used together as a supercomputer to provide a solution. In this paper, a PC cluster consisting of one master node and nine disk-less slave nodes (10 processors), is proposed and built for parallel rendering purposes. The system architecture and benchmark performances of this cluster are also presented. Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. Harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. Also, in this paper, we construct two heterogeneous PC clusters for parallel rendering purpose and install Linux Red Hat 9 on each PC cluster. Then, these clusters are set to the different subnet. Therefore, we use the grid middleware lambdaobus ToolKit, to connect these two clusters to form a grid computing environment on multiple Linux PC clusters. We also install the SUN Grid Engine, to manage and monitor incoming or outgoing computing jobs and schedule the job to achieve high performance computing and high CPU utilization. The system architecture and benchmark performances of this cluster are also presented
  • Keywords
    Linux; distributed memory systems; grid computing; middleware; processor scheduling; rendering (computer graphics); resource allocation; workstation clusters; CPU utilization; Globus ToolKit; Internet computing; Linux PC clusters; Linux Red Hat 9; PC cluster; SUN Grid Engine; cluster computing; cluster machines; computational resources; computing job monitoring; computing job schedule; data resources; disk-less slave node processors; grid computing; grid computing environment; grid middleware; heterogeneous PC clusters; institutional boundaries; large-scale resource aggregation; master node; parallel 3D rendering; resource sharing; subnet cluster setting; supercomputer; system architecture; system benchmark performances; Computer architecture; Grid computing; High performance computing; Internet; Large-scale systems; Linux; Master-slave; Middleware; Physics; Supercomputers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    0-7803-8603-5
  • Type

    conf

  • DOI
    10.1109/ICME.2004.1394336
  • Filename
    1394336