1 / 11

High-Performance Visualization of Geographic Data

Explore the convergence of GIS and high-performance computing, showcasing the use of new technologies for dynamic data analysis, data mining, and visual exploration methods in geographic information systems. Learn about visualization architectures, software, and tools, such as EVEREST visualization cluster, pd-GRASS, and GRASS+SLURM.

adana
Download Presentation

High-Performance Visualization of Geographic Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. High-Performance Visualization of Geographic Data Budhendra Bhaduri Alexandre Sorokine Geographic Information Science and Technology Computational Sciences and Engineering

  2. Geographic information systems:A short introduction • GIS = Geographic information system • Information system to manage geographic data • Uses • Data integration, analysis, modeling, and visualization • Example Applications • Government • Homeland security • Resource management • Environmental management • …

  3. GIS and high-performance computing:Incentives for convergence • Growing size of geographic databases (TB per day) • Hi-res satellite imagery • Sensor networks • LIDAR, SAR, MODIS and other sensor platforms • Integration of multiple data sources • In Internet applications • Using OpenGIS standards • New technologies for scientific computing • Dynamic data analysis • Data mining and visual exploratory methods • Simulation models

  4. Rendering Node Display Display Display Display Rendering Node Rendering Node Rendering Node High-performance visualization architecture for GIS • EVEREST visualization cluster • 30x8 foot viewing area • 11,5303,072 pixel array (35 MP) • 27 digital light projectors • 15 rendering nodes • Software • OS SUSE Linux • Xdmx distributed X server • GRASS GIS

  5. pd-GRASS: Parallel display for GRASS GIS • GRASS GIS • Free GIS package • No license fees • Works on Linux • pd-GRASS • GRASS module for parallel visualization • Full parallelization • Tested with datasets of up to 40 GB • Full GRASS GIS functionality • Available under GPL from http://www.ornl.gov/gist/software/grass/

  6. pd-GRASS visualization example: beyond desktop capabilities Shuttle Radar Topography Mission (SRTM) dataset • 90m cell size • About 3109 pixel • Approximately 7GB

  7. High-resolution 3-D View of LIDAR data:beyond desktop capabilities LIDAR dataset for the city of Houston • Resolution: 3cm horizontal, 1cm vertical • 108 cells • Approximately 4 GB Data Courtesy: Center for Space Research, UT Austin

  8. Parallel Geospatial Computing • Uses • Processing of large datasets • Visual analytics of dynamic data • Rendering of scientific animations • Tools • GRASS+SLURM • GRASS=Free Linux-based GIS • SLURM=Simple Linux Utility for Resource Management • Computational domain decomposition • By data layer • By function • By geographic region • Application Example • Animated display decluttering for the south-east US electric grid

  9. High-performance visualization of agent-based transportation models • Meso- and macro-scale models • Testing evacuation scenarios • Up to a million links

  10. Geospatial analytics:Visual exploration and inferencing for dynamic geographic data Geographic spread of socio-economic and environmental processes and events • History of the U.S. electric infrastructure • Scenarios for development of nuclear power production

  11. Contacts • Budhendra Bhaduri • Geographic Information Science and Tech • Computational Sciences and Engineering • (865) 241-9272 • bhaduribl@ornl.gov • Alexandre Sorokine • Geographic Information Science and Tech • Computational Sciences and Engineering • (865) 576-7597 • sorokina@ornl.gov 11 Bhaduri_HPC_GIS_Viz_SC07

More Related