Supercomputing

This page aims to

• overview installations of GRASS GIS in supercomputing (HPC, HTC) environments and related applications
• document best practices of processing big geospatial data, common mistakes and errors and how to work-around them

Overview of GRASS GIS in supercomputing environments

• Supercomputer "Aurel", 4096 CPU cores (Power7 architecture), features GRASS GIS 7.4
• GRASS GIS in JRC's JEODPP, A versatile data-intensive computing platform for information retrieval from big geospatial data

See also

Related wiki pages

• https://grasswiki.osgeo.org/wiki/Parallel_GRASS_jobs
• https://grasswiki.osgeo.org/wiki/Working_with_GRASS_without_starting_it_explicitly
• https://grasswiki.osgeo.org/wiki/GRASS_and_Shell
• https://grasswiki.osgeo.org/wiki/GRASS_GIS_Performance
• https://grasswiki.osgeo.org/wiki/Large_raster_data_processing
• https://grasswiki.osgeo.org/wiki/Large_vector_data_processing

Presentations

• https://fosdem.org/2018/schedule/event/geo_grass/
• https://archive.fosdem.org/2015/schedule/event/grass_7/
• State of GIS at the High Performance Computing Cluster (2012)

Publications

• Alvioli, M., A. C. Mondini, F. Fiorucci, M. Cardinali & I. Marchesini (2018) Topography-driven satellite imagery analysis for landslide mapping, Geomatics, Natural Hazards and Risk, 9:1, 544-567, DOI: 10.1080/19475705.2018.1458050
• Delucchi, L., Neteler, M. (2011): g.cloud module for GRASS GIS, FOSS4G 2011 Denver, Slides: https://www.slideshare.net/lucadelu/grass-cloud
• Neteler, M. (2008): Building a cluster for GRASS GIS and other software from the OSGeo stack, https://courses.neteler.org/building-a-cluster-for-grass-gis-and-other-software-from-the-osgeo-stack/

Upcoming in 2018:

• Special issue "High-Performance Computing in Geoscience and Remote Sensing", Sensors (ISSN 1424-8220; CODEN: SENSC9)