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
Processing Practices
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
- Special issue "High-Performance Computing in Geoscience and Remote Sensing", Sensors (ISSN 1424-8220; CODEN: SENSC9)
- https://doi.org/10.1080/19475705.2018.1458050