Supercomputing: Difference between revisions

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(GRASS GIS 8 on LUMI Supercomputer in Finland)
 
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* [https://vs.sav.sk/?lang=en&section=departments&sub=vvt&sub2=services Supercomputer "Aurel"], 4096 CPU cores (Power7 architecture), features GRASS GIS 7.4
* [https://vs.sav.sk/?lang=en&section=departments&sub=vvt&sub2=services Supercomputer "Aurel"], 4096 CPU cores (Power7 architecture), features GRASS GIS 7.4
* GRASS GIS in JRC's JEODPP, [https://doi.org/10.1016/j.future.2017.11.007 A versatile data-intensive computing platform for information retrieval from big geospatial data]
* GRASS GIS in JRC's JEODPP, [https://doi.org/10.1016/j.future.2017.11.007 A versatile data-intensive computing platform for information retrieval from big geospatial data]
* [https://projects.ncsu.edu/hpc/Software/Software.php henry2 at NCSU] (Intel Xeon based Linux cluster; GRASS GIS 7.2.0 installed around 2017)
* [https://hpc.ncsu.edu/Software/Apps.php?app=gis Hazel at NCSU] (Intel Xeon based Linux cluster; GRASS GIS available since 2017)
 
Past:
 
* [https://wiki.ncsa.illinois.edu/pages/viewpage.action?pageId=47294247 ROGER, the CyberGIS supercomputer] at NCSA UIUC (batch compute nodes: 24x, 10 cores, 2.6 GHz, 256 GB RAM, 500 GB of local storage, cluster-wide General Parallel File System (GPFS) 4.5PB; GRASS GIS available alongside GDAL, PDAL, Geotools, and R)
* [https://wiki.ncsa.illinois.edu/pages/viewpage.action?pageId=47294247 ROGER, the CyberGIS supercomputer] at NCSA UIUC (batch compute nodes: 24x, 10 cores, 2.6 GHz, 256 GB RAM, 500 GB of local storage, cluster-wide General Parallel File System (GPFS) 4.5PB; GRASS GIS available alongside GDAL, PDAL, Geotools, and R)



Latest revision as of 14:17, 19 February 2024

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

Past:

  • ROGER, the CyberGIS supercomputer at NCSA UIUC (batch compute nodes: 24x, 10 cores, 2.6 GHz, 256 GB RAM, 500 GB of local storage, cluster-wide General Parallel File System (GPFS) 4.5PB; GRASS GIS available alongside GDAL, PDAL, Geotools, and R)

Processing Practices

See page Parallel GRASS jobs for Cluster and Grid computing with parallelized code, Job scheduler, and GRASS on a cluster

See also

Related wiki pages

Presentations

Publications

Upcoming in 2018:

Miscellaneous