Implementation of a parallel high-performance visualization technique in GRASS GIS

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper describes an extension for GRASS geographic information systems (GIS) that enables users to perform geographic visualization tasks on tiled high-resolution displays powered by the clusters of commodity personal computers. Parallel visualization systems are becoming more common in scientific computing due to the decreasing hardware costs and availability of the open source software to support such architecture. High-resolution displays allow scientists to visualize very large data sets with minimal loss of details. Such systems have a big promise especially in the field of GIS because users can naturally combine several geographic scales on a single display. This paper discusses architecture, implementation, and operation of pd-GRASS-a GRASS GIS extension for high-performance parallel visualization on tiled displays. pd-GRASS is specifically well suited for very large geographic data sets, such as light detecting and ranging data or high-resolution nation-wide geographic databases. This paper also briefly touches on computational efficiency, performance, and potential applications for such systems.

Original languageEnglish
Pages (from-to)685-695
Number of pages11
JournalComputers and Geosciences
Volume33
Issue number5
DOIs
StatePublished - May 2007

Funding

Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), managed by UT-Battelle, LLC for the US Department of Energy under Contract No. DE-AC05-00OR22725. This research used resources of the National Center for Computational Sciences at Oak Ridge National Laboratory, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725.

Keywords

  • Geographic information systems
  • High-performance computing
  • Open source software
  • Visualization

Fingerprint

Dive into the research topics of 'Implementation of a parallel high-performance visualization technique in GRASS GIS'. Together they form a unique fingerprint.

Cite this