snowfall-b-init: Initialisation of cluster usage

snowfall-initR Documentation

Initialisation of cluster usage


Initialisation and organisation code to use snowfall.


sfInit( parallel=NULL, cpus=NULL, type=NULL, socketHosts=NULL, restore=NULL,
        slaveOutfile=NULL, nostart=FALSE, useRscript=FALSE )
sfStop( nostop=FALSE )

sfSetMaxCPUs( number=32 )



Logical determinating parallel or sequential execution. If not set values from commandline are taken.


Numerical amount of CPUs requested for the cluster. If not set, values from the commandline are taken.


Logical determinating if the basic cluster setup should be skipped. Needed for nested use of snowfall and usage in packages.


Type of cluster. Can be 'SOCK', 'MPI', 'PVM' or 'NWS'. Default is 'SOCK'.


Host list for socket clusters. Only needed for socketmode (SOCK) and if using more than one machines (if using only your local machine (localhost) no list is needed).


Globally set the restore behavior in the call sfClusterApplySR to the given value.


Write R slave output to this file. Default: no output (Unix: /dev/null, Windows: :nul). If using sfCluster this argument has no function, as slave logs are defined using sfCluster.


Change startup behavior (snow>0.3 needed): use shell scripts or R-script for startup (R-scripts beeing the new variant, but not working with sfCluster.


Same as noStart for ending.


Amount of maximum CPUs useable.


sfInit initialisise the usage of the snowfall functions and - if running in parallel mode - setup the cluster and snow. If using sfCluster management tool, call this without arguments. If sfInit is called with arguments, these overwrite sfCluster settings. If running parallel, sfInit set up the cluster by calling makeCluster from snow. If using with sfCluster, the initialisation also contains management of lockfiles. If this function is called more than once and current cluster is yet running, sfStop is called automatically.

Note that you should call sfInit before using any other function from snowfall, with the only exception sfSetMaxCPUs. If you do not call sfInit first, on calling any snowfall function sfInit is called without any parameters, which is equal to sequential mode in snowfall only mode or the settings from sfCluster if used with sfCluster.

This also means, you cannot check if sfInit was called from within your own program, as any call to a function will initialize again. Therefore the function sfIsRunning gives you a logical if a cluster is running. Please note: this will not call sfInit and it also returns true if a previous running cluster was stopped via sfStop in the meantime.

If you use snowfall in a package argument nostart is very handy if mainprogram uses snowfall as well. If set, cluster setup will be skipped and both parts (package and main program) use the same cluster.

If you call sfInit more than one time in a program without explicit calling sfStop, stopping of the cluster will be executed automatically. If your R-environment does not cover required libraries, sfInit automatically switches to sequential mode (with a warning). Required libraries for parallel usage are snow and depending on argument type the libraries for the cluster mode (none for socket clusters, Rmpi for MPI clusters, rpvm for PVM clusters and nws for NetWorkSpaces).

If using Socket or NetWorkSpaces, socketHosts can be used to specify the hosts you want to have your workers running. Basically this is a list, where any entry can be a plain character string with IP or hostname (depending on your DNS settings). Also for real heterogenous clusters for any host pathes are setable. Please look to the acccording snow documentation for details. If you are not giving an socketlist, a list with the required amount of CPUs on your local machine (localhost) is used. This would be the easiest way to use parallel computing on a single machine, like a laptop.

Note there is limit on CPUs used in one program (which can be configured on package installation). The current limit are 32 CPUs. If you need a higher amount of CPUs, call sfSetMaxCPUs before the first call to sfInit. The limit is set to prevent inadvertently request by single users affecting the cluster as a whole.

Use slaveOutfile to define a file where to write the log files. The file location must be available on all nodes. Beware of taking a location on a shared network drive! Under *nix systems, most likely the directories /tmp and /var/tmp are not shared between the different machines. The default is no output file. If you are using sfCluster this argument have no meaning as the slave logs are always created in a location of sfClusters choice (depending on it's configuration).

sfStop stop cluster. If running in parallel mode, the LAM/MPI cluster is shut down.

sfParallel, sfCpus and sfSession grant access to the internal state of the currently used cluster. All three can be configured via commandline and especially with sfCluster as well, but given arguments in sfInit always overwrite values on commandline. The commandline options are --parallel (empty option. If missing, sequential mode is forced), --cpus=X (for nodes, where X is a numerical value) and --session=X (with X a string).

sfParallel returns a logical if program is running in parallel/cluster-mode or sequential on a single processor.

sfCpus returns the size of the cluster in CPUs (equals the CPUs which are useable). In sequential mode sfCpus returns one. sfNodes is a deprecated similar to sfCpus.

sfSession returns a string with the session-identification. It is mainly important if used with the sfCluster tool.

sfGetCluster gets the snow-cluster handler. Use for direct calling of snow functions.

sfType returns the type of the current cluster backend (if used any). The value can be SOCK, MPI, PVM or NWS for parallel modes or "- sequential -" for sequential execution.

sfSocketHosts gives the list with currently used hosts for socket clusters. Returns empty list if not used in socket mode (means: sfType() != 'SOCK').

sfSetMaxCPUs enables to set a higher maximum CPU-count for this program. If you need higher limits, call sfSetMaxCPUs before sfInit with the new maximum amount.

See Also

See snow documentation for details on commands: link[snow]{snow-cluster}


## Not run: 
  # Run program in plain sequential mode.
  sfInit( parallel=FALSE )
  stopifnot( sfParallel() == FALSE )

  # Run in parallel mode overwriting probably given values on
  # commandline.
  # Executes via Socket-cluster with 4 worker processes on
  # localhost.
  # This is probably the best way to use parallel computing
  # on a single machine, like a notebook, if you are not
  # using sfCluster.
  # Uses Socketcluster (Default) - which can also be stated
  # using type="SOCK".
  sfInit( parallel=TRUE, cpus=4 )
  stopifnot( sfCpus() == 4 )
  stopifnot( sfParallel() == TRUE )

  # Run parallel mode (socket) with 4 workers on 3 specific machines.
  sfInit( parallel=TRUE, cpus=4, type="SOCK",
          socketHosts=c( "biom7", "biom7", "biom11", "biom12" ) )
  stopifnot( sfCpus() == 4 )
  stopifnot( sfParallel() == TRUE )

  # Hook into MPI cluster.
  # Note: you can use any kind MPI cluster Rmpi supports.
  sfInit( parallel=TRUE, cpus=4, type="MPI" )

  # Hook into PVM cluster.
  sfInit( parallel=TRUE, cpus=4, type="PVM" )

  # Run in sfCluster-mode: settings are taken from commandline:
  # Runmode (sequential or parallel), amount of nodes and hosts which
  # are used.

  # Session-ID from sfCluster (or XXXXXXXX as default)
  session <- sfSession()

  # Calling a snow function: cluster handler needed.
  parLapply( sfGetCluster(), 1:10, exp )

  # Same using snowfall wrapper, no handler needed.
  sfLapply( 1:10, exp )


## End(Not run)

snowfall documentation built on July 5, 2022, 5:07 p.m.