GRASS GIS in the Cloud



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Transcription:

GRASS GIS in the Cloud Fondazione Edmund Mach GIS & Remote Sensing Platform http://gis.cri.fmach.it XIII Meeting GRASS e GFOSS 17th February 2012, Trieste (Italy)

Cloud Our cluster Cloud Cloud computing is the delivery of computing as a service rather than a product, whereby shared resources, software and information are provided to computers and other devices as a utility over a network Wikipedia

Cloud Our cluster Cluster A computer cluster is a group of linked computers, working together closely thus in many respects forming a single computer. Clusters are usually deployed to improve performance and availability over that of a single computer Wikipedia

Introduction Cloud Our cluster Our cluster: infrastructure FEM GIS cluster consists of 300 nodes 610 GB RAM 34 TB disk storage + 15 TB tape backup 10 Gb/s internal bus Scientific Linux 6.2 Grid Engine

Cloud Our cluster Our cluster: massive spatial data analysis MODIS Land Surface Temperature (LST) map gap-filling (13,000 maps) MODIS data analysis (LST, NDVI, Snow products) LiDAR data analysis Solar energy calculations Neteler et al., 2011: Tiger mosquito, IJHG, doi:10.1186/1476-072x-10-49

to facilitate GRASS GIS usage on a cluster Simplify the work

to facilitate GRASS GIS usage on a cluster Simplify the work Offer the possibility to use Grid Engine by all our colleagues

to facilitate GRASS GIS usage on a cluster Simplify the work Offer the possibility to use Grid Engine by all our colleagues Launch jobs remotely without connecting every time to the cluster

to facilitate GRASS GIS usage on a cluster Simplify the work Offer the possibility to use Grid Engine by all our colleagues Launch jobs remotely without connecting every time to the cluster Offer the possibility to external people to use the cluster without learning Grid Engine

: requirements GRASS GIS 7 (current development version)

: requirements GRASS GIS 7 (current development version) Grid Engine

: requirements GRASS GIS 7 (current development version) Grid Engine Python > 2.4

: how does it work? Required parameters (if you want launch jobs) conf = file with username and password or stdin to connect to the cluster

: how does it work? Required parameters (if you want launch jobs) conf = file with username and password or stdin to connect to the cluster server = hostname of the cluster

: how does it work? Required parameters (if you want launch jobs) conf = file with username and password or stdin to connect to the cluster server = hostname of the cluster qsub script = file containing qsub script (template)

: how does it work? Required parameters (if you want launch jobs) conf = file with username and password or stdin to connect to the cluster server = hostname of the cluster qsub script = file containing qsub script (template) grass script = own GRASS GIS script

: how does it work? Required parameters (if you want launch jobs) conf = file with username and password or stdin to connect to the cluster server = hostname of the cluster qsub script = file containing qsub script (template) grass script = own GRASS GIS script g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test novariables.sh

: how does it work? Optional parameters raster = name of raster(s)

: how does it work? Optional parameters raster = name of raster(s) vector = name of vector(s)

: how does it work? Optional parameters raster = name of raster(s) vector = name of vector(s) variables = string with name and values of variables stated as Python dictionary key :[ value0, value1 ]

: how does it work? Optional parameters raster = name of raster(s) vector = name of vector(s) variables = string with name and values of variables stated as Python dictionary key :[ value0, value1 ] email = user s email address

: how does it work? Optional parameters raster = name of raster(s) vector = name of vector(s) variables = string with name and values of variables stated as Python dictionary key :[ value0, value1 ] email = user s email address reconnect = reconnect with old job to see if it is finished and move the output data back on the client

: how does it work? Optional parameters raster = name of raster(s) vector = name of vector(s) variables = string with name and values of variables stated as Python dictionary key :[ value0, value1 ] email = user s email address reconnect = reconnect with old job to see if it is finished and move the output data back on the client path = path to the folder which must be accessible from cluster frontend and blades

: how does it work? Flags c = cycle through all variables

: how does it work? Flags c = cycle through all variables k = keep temporal files and mapsets

: how does it work? Flags c = cycle through all variables k = keep temporal files and mapsets a = use ssh-add for faster access

: more examples North Carolina sample data r.texture example g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test onevariable raster.sh variables= TEXT : [ asm, contrast, corr,var, idm, sa, se, sv, entr, dv, de, moc1, moc2 ] raster=lsat7 2002 40

: more examples North Carolina sample data r.texture example g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test onevariable raster.sh variables= TEXT : [ asm, contrast, corr,var, idm, sa, se, sv, entr, dv, de, moc1, moc2 ] raster=lsat7 2002 40 r.sun example g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test onevariable sun.sh variables= DOY : [1,2,3,4,5,6,7,8,9,10] raster=elevation

: more examples more variable example g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test morevariables sun.sh variables= NPOINT : [10,20], BUFFERDIST : [100,500] use number point 10 with buffer distance 100; and number point 20 with buffer distance 500

: more examples more variable example g.cloud conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test morevariables sun.sh variables= NPOINT : [10,20], BUFFERDIST : [100,500] use number point 10 with buffer distance 100; and number point 20 with buffer distance 500 more variable example g.cloud -c conf=/tmp/passwd server=giscluster qsub script=test launch SGE grassjob.sh grass script=test morevariables sun.sh variables= NPOINT : [10,20], BUFFERDIST : [100,500] use number point 10 with buffer distance 100 and 500; number point 20 with buffer distance 100 and 500

: reconnect North Carolina sample data reconnect example g.cloud conf=/tmp/passwd server=giscluster reconnect=tmpfeq4ck

: future Support for more clustering system (for example Eucalyptus)

: future Support for more clustering system (for example Eucalyptus) Auto installation of GRASS and its dependencies on the cluster if not present (GRASS 7 release as stable version)

: future Support for more clustering system (for example Eucalyptus) Auto installation of GRASS and its dependencies on the cluster if not present (GRASS 7 release as stable version) Show the status of jobs

First implementation of a module to run GRASS on a cluster

First implementation of a module to run GRASS on a cluster Experimental version

First implementation of a module to run GRASS on a cluster Experimental version Please test it and report bugs or improvements

First implementation of a module to run GRASS on a cluster Experimental version Please test it and report bugs or improvements Contact us for more info markus.neteler@iasma.it - luca.delucchi@iasma.it

Thanks for your attention gis.cri.fmach.it