Participants:

• Marcus Thiebaux (USC-ISI Center for Grid Technologies)
• Hongsuda Tangmunarunkit (USC-ISI Center for Grid Technologies)
• Karl Czajkowski (USC-ISI Center for Grid Technologies)
• Carl Kesselman (USC-ISI Center for Grid Technologies)

Advance in sciences and engineerings has put high demand on tools for high-performance large-scale visual data exploration and analysis. For example, earthquake scientists can now study the earthquake phonomena from first principle physic-based simulations. These simulations can generate large amount of data, possibly with high resolution (in three dimensional space) and long time series. Single-system visualization software running on commodity machines cannot scale up to the large amount of data generated by these simulations. To address this problem, we propose a flexible and extensible Grid-based visualization framework for time-critical, interactively controlled file-set transfer for visual browsing of spatially and temporally large datasets in a Grid environment. Our framework leverages Grid resources for scalable computation and data storage to enhance the performance, functionality and flexibility of the light-weight single system tool.

Our framework utilizes Globus Toolkit 2.4 components for security (i.e., GSI), resource allocation and management (i.e., DUROC, GRAM) and communication (i.e., Globus-IO) to couple commodity desktops with remote, scalable storage and computational resources in a Grid for interactive data exploration. There are two major components in this framework---Grid Data Transport (GDT) and the Grid Visualization Utility (GVU). GDT provides libraries for performing parallel data filtering and parallel data exchange among Grid resources. GDT allows arbitrary data filtering to be integrated into the system. It also facilitates multi-tiered pipeline topology construction of compute resources and displays. In addition to scientific visualization applications, GDT can be used to support other applications that require parallel processing and parallel transfer of partial ordered independent files, such as file-set transfer.

On top of GDT, we have developed the Grid Visualization Utility (GVU), which is designed to assist visualization dataset management, including file formatting, data transport and automatic byte swapping. GVU also supports parameterized data reduction filters such as point sampling with scalar range culling, as well as volume cropping, and down sampling. The GVU framework can be used to facilitate the parallel execution of existing transformation filters, such as the VTK marching cubes isosurface filter, as well as other custom domain-specific filters. Our initial implementation supports remote systhesis of view point independent display lists. This feature allows the local display machine to control the view point for reduced view point latency, and multi-view rendering (e.g., stereo rendering).

Architecture

Hardware & Software Requirements

Client Machine

• Hardware
  • Linux OS machine
  • >= 1GB of memory
  • High-performance graphic cards such as Nvidia, etc.
• Software
  • Globus 2.4.3* (client with gcc32dbgpthr flavor) including Globus IO, GRAM and DUROC.
  • OpenGL library
  • Glut library

• Hardware
  • Linux systems
• Software
  • Globus 2.4.3* (with gcc32dbgpthr flavor) including Globus IO, GRAM and DUROC.
  • Globus Gatekeeper (for remote job submission)

Publications

• M. Thiebaux, H. Tangmunarunkit, K. Czajkowski, C. Kesselman, "Scalable Grid-based Visualization Framework", Submitted for High Performance Distributed Computing 2004. pdf and ps


• K. Czajkowski, M. Thiebaux, C. Kesselman, "Practical Resource Management for Grid-based Visual Exploration", High Performance Distributed Computing 2001. pdf

Presentations

• NASA IPG 2003

Posters

• AGU Meeting 2003, Dec 8-12, 2003
• SCEC Annual Meeting 2003, Sept 2003

Related Material

• SCEC Community Modeling Environment. SC03 Handout (ppt, pdf, ps)

Related Links

• USC-ISI Center for Grid Technologies
• SCEC Community Modeling Environment

Projects that benefit from our visualization tools

• Southern California Earthquake Center - ITR project
  • Community Velocity Model
    • SCEC Community Velocity Model: P-wave velocity in Southern California. ( jpg )
      
      
      
    • SCEC Community Velocity Model: S-wave velocity in Southern California. ( jpg )
      
      
      
  • Fault Rupture Dynamic Model
    
    • Velocity magnitude of Geof Ely's fault rupture simulation through a uniform earth (Time Step = 1500 from 3000). ( jpg , bmp )
      
      
    • Cross-eye stereo pair images of the velocity magnitude of Geof Ely's fault rupture simulation through a uniform earth (Time Step = 1500 from 3000). ( jpg , bmp )
      
      
      
  • Anelastic Wave Propagation Model
    • Velocity in Y-direction from Kim Olsen's wave propagation model (simulating the Northridge Earthquake). ( jpg )
      
      
      
  • Fretchet Kernel Analysis
    • Li Zhao's Fretchet Kernel Movies
• Optiputer Project