Supercomputing - Revision history

Wenzeslaus: /* Overview of GRASS GIS in supercomputing environments */ add past section, update NCSU

2024-02-19T14:17:01Z

Overview of GRASS GIS in supercomputing environments: add past section, update NCSU

← Older revision		Revision as of 14:17, 19 February 2024
Line 9:		Line 9:
	* [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)

Neteler: GRASS GIS 8 on LUMI Supercomputer in Finland

2024-02-19T13:29:51Z

GRASS GIS 8 on LUMI Supercomputer in Finland

← Older revision		Revision as of 13:29, 19 February 2024
Line 6:		Line 6:
	= Overview of GRASS GIS in supercomputing environments =		= Overview of GRASS GIS in supercomputing environments =

			* GRASS GIS 8 on LUMI Supercomputer in Finland: https://docs.csc.fi/apps/grass/
	* [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://projects.ncsu.edu/hpc/Software/Software.php henry2 at NCSU] (Intel Xeon based Linux cluster; GRASS GIS 7.2.0 installed around 2017)
	* [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)

⚠️NikosA: Link to "European High-Performance Computing Joint Undertaking"

2018-05-29T13:16:42Z

Link to "European High-Performance Computing Joint Undertaking"

← Older revision		Revision as of 13:16, 29 May 2018
Line 39:		Line 39:
	Upcoming in 2018:		Upcoming in 2018:
	* [http://www.mdpi.com/si/15134 Special issue "High-Performance Computing in Geoscience and Remote Sensing"], Sensors (ISSN 1424-8220; CODEN: SENSC9)		* [http://www.mdpi.com/si/15134 Special issue "High-Performance Computing in Geoscience and Remote Sensing"], Sensors (ISSN 1424-8220; CODEN: SENSC9)

			== Miscellaneous ==

			* [http://europa.eu/!qk37Tr The European High-Performance Computing Joint Undertaking - EuroHPC]

Neteler: +link to Parallel GRASS jobs

2018-05-24T20:41:29Z

+link to Parallel GRASS jobs

← Older revision		Revision as of 20:41, 24 May 2018
Line 12:		Line 12:

	= Processing Practices =		= Processing Practices =

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

	= See also =		= See also =

⚠️Wenzeslaus: /* Overview of GRASS GIS in supercomputing environments */ add NCSU and NCSA UIUC

2018-05-23T20:14:23Z

Overview of GRASS GIS in supercomputing environments: add NCSU and NCSA UIUC

← Older revision		Revision as of 20:14, 23 May 2018
Line 8:		Line 8:
	* [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://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)

	= Processing Practices =		= Processing Practices =

Neteler: expanded

2018-05-23T16:03:52Z

expanded

← Older revision		Revision as of 16:03, 23 May 2018
Line 29:		Line 29:

	== Publications ==		== 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: [https://doi.org/10.1080/19475705.2018.1458050 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:
	* [http://www.mdpi.com/si/15134 Special issue "High-Performance Computing in Geoscience and Remote Sensing"], Sensors (ISSN 1424-8220; CODEN: SENSC9)		* [http://www.mdpi.com/si/15134 Special issue "High-Performance Computing in Geoscience and Remote Sensing"], Sensors (ISSN 1424-8220; CODEN: SENSC9)
	* https://doi.org/10.1080/19475705.2018.1458050

⚠️NikosA: More links collected from related thread in the grass-user mailing list

2018-05-23T12:28:44Z

More links collected from related thread in the grass-user mailing list

← Older revision		Revision as of 12:28, 23 May 2018
Line 5:		Line 5:

	= Overview of GRASS GIS in supercomputing environments =		= Overview of GRASS GIS in supercomputing environments =

			* [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]

	= Processing Practices =		= Processing Practices =
Line 23:		Line 26:
	* https://fosdem.org/2018/schedule/event/geo_grass/		* https://fosdem.org/2018/schedule/event/geo_grass/
	* https://archive.fosdem.org/2015/schedule/event/grass_7/		* https://archive.fosdem.org/2015/schedule/event/grass_7/
			* [http://gfzpublic.gfz-potsdam.de/pubman/item/escidoc:100071:1/component/escidoc:100070/5_GISDAY-2012_loewe_thaler_State_of_the_Cluster_bib.pdf%3Bjsessionid=87D8757B6257885C6 State of GIS at the High Performance Computing Cluster (2012)]

			== Publications ==

			* [http://www.mdpi.com/si/15134 Special issue "High-Performance Computing in Geoscience and Remote Sensing"], Sensors (ISSN 1424-8220; CODEN: SENSC9)
			* https://doi.org/10.1080/19475705.2018.1458050

⚠️NikosA: Creation of a page for GRASS GIS and supercomputing (HPC, HTC)

2018-05-23T12:13:52Z

Creation of a page for GRASS GIS and supercomputing (HPC, HTC)

New page

This page aims to

* '''overview''' installations of GRASS GIS in [https://en.wikipedia.org/wiki/Supercomputer 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 =

= 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/