		 SNOW: Simple Network of Workstations

The snow package provides support for simple parallel computing on a
network of workstations using R.  A master R process calls makeCluster
to start a cluster of slave processes; the master process then uses
functions such as clusterCall and clusterApply to execute R code on
the slave processes and collect and return the results on the master.
This framework supports many forms of "embarrassingly parallel"
computations.

Snow can use one of three communications mechanisms: sockets, PVM, or
MPI.  PVM clusters use the rpvm package; MPI clusters use package
Rmpi.  If pvm is used, then pvm must be started, either using a pvm
console (e.g the pvm text console or the graphical xpvm console, both
available with pvm) or from R using functions provided by rpvm.
Similarly, LAM-MPI must be started, e.g. using lamboot, for MPI
clusters that use Rmpi and LAM-MPI.


			       CAUTION

Be sure to call stopCluster before exiting R.  Otherwise stray
processes may remain running and need to be shut down manually.


			     INSTALLATION

PVM clusters require PVM and the rpvm package.  MPI clusters require
LAM-MPI and the Rmpi package.  The rsprng and/or rlecuyer packages may
also be useful to support parallel random number generation.  These
supporting R packages and the snow package should be installed in the
same library directory.  The snow package and supporting packages need
to be available on all hosts that are to be used for a cluster.

No further configuration should be needed for a homogeneous network of
workstations with a common architecture and common file system layout.
If some hosts have different file system layouts, then the file
RunSnowNode should be placed in a directory on the PATH of each host
to be used for slave processes, and each such host should define the
variable R_SNOW_LIB as the directory in which the snow package and
supporting packages have been installed.  Thus if snow has been
installed with

	R CMD INSTALL snow -l $HOME/SNOW/R/lib

then users with a csh shell would place something like

	setenv R_SNOW_LIB $HOME/SNOW/R/lib

in their .cshrc files.  Setting this variable to a nonempty value on
the master as well insures that the cluster startup mechanism assumes
an inhomogeneous cluster by default.  R should also be on the PATH of
the hosts used to run slave processes (alternatively, you can edit the
RunSnowNode scripts to use a fully qualified path to the R shell
script).

To date, snow has been used successfully with master and slaves running
on combinations of several flavors of Unix-like operating systems,
including Linux, HP-UX and Mac OS X using PVM, LAM-MPI, or sockets.
The socket version of snow has also been run with a master on Windows
and slaves on Linux.  Reports on further experiences with Windows
systems would be welcome.


			      REFERENCE

http://www.stat.uiowa.edu/~luke/R/cluster/cluster.html.
