Support for simple parallel computing in R Maintained by:tota@FreeBSD.org Port Added: 31 Jan 2012 13:14:46 License: not specified in port
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 worker processes; the master process then uses
functions such as clusterCall and clusterApply to execute R code on
the worker processes and collect and return the results on the master.
This framework supports many forms of "embarrassingly parallel"
computations.
Snow can use one of four communications mechanisms: sockets, PVM, MPI,
or NetWorkSpaces (NWS). NWS support was provided by Steve Weston.
PVM clusters use the rpvm package; MPI clusters use package Rmpi; NWS
clusters use package nws. 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. If NWS is used,
the NetWorkSpaces server must be running. SOCK clusters are the
easiest approach for using snow on a single multi-core computer as
they require no additional software.
WWW: http://cran.r-project.org/web/packages/snow/
- update math/R-cran-psych to 1.2.1 [1]
- update math/R to 2.15.0, and adjust dependent ports
- minor changes to bsd.cran.mk [2]: rename MASTER_CRAN_SITES to
MASTER_SITE_CRAN, as in bsd.sites.mk; make the install target more
flexible and allow CRAN ports to override it; add a regression-test
target; set USE_FORTRAN to match math/R; remove some of the
redundant checks of USE_R_MOD; honor NOPORTDATA and NOPORTDOCS
Reviewed by: thierry, tota, wen
Approved by: D. Rue (maintainer) [1], wen [2]
- Add a new port: science/R-cran-snow
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 worker processes; the master process then uses
functions such as clusterCall and clusterApply to execute R code on
the worker processes and collect and return the results on the master.
This framework supports many forms of "embarrassingly parallel"
computations.
Snow can use one of four communications mechanisms: sockets, PVM, MPI,
or NetWorkSpaces (NWS). NWS support was provided by Steve Weston.
PVM clusters use the rpvm package; MPI clusters use package Rmpi; NWS
clusters use package nws. 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. If NWS is used,
the NetWorkSpaces server must be running. SOCK clusters are the
easiest approach for using snow on a single multi-core computer as
they require no additional software.
WWW: http://cran.r-project.org/web/packages/snow/
