The doParallel Package
Description
The doParallel package provides a parallel backend for the foreach/%dopar%
function using the parallel package of R 2.14.0 and later.
Details
Further information is available in the following help topics:
registerDoParallel |
register doParallel to be used by foreach/%dopar% |
|
|
To see a tutorial introduction to the doParallel package,
use vignette("gettingstartedParallel"). To see a tutorial
introduction to the foreach package, use vignette("foreach").
To see a demo of doParallel computing the sinc function,
use demo(sincParallel).
Some examples (in addition to those in the help pages) are included in
the “examples” directory of the doParallel package. To list the files in
the examples directory,
use list.files(system.file("examples", package="doParallel")).
To run the bootstrap example, use
source(system.file("examples", "bootParallel.R", package="doParallel")).
This is a simple benchmark, executing both sequentally and in parallel.
There are many more examples that come with the foreach package,
which will work with the doParallel package if it is registered as the
parallel backend.
For a complete list of functions with individual help pages,
use library(help="doParallel").
registerDoParallel
Description
The registerDoParallel function is used to register the
parallel backend with the foreach package.
Usage
registerDoParallel(cl, cores=NULL, ...)
stopImplicitCluster()
Arguments
cl |
A cluster object as returned by makeCluster, or the number
of nodes to be created in the cluster. If not specified, on Windows a
three worker cluster is created and used.
|
cores |
The number of cores to use for parallel execution. If not
specified, the number of cores is set to the value of
options("cores"), if specified, or to one-half the number of cores detected
by the parallel package.
|
... |
Package options. Currently, only the nocompile option
is supported. If nocompile is set to TRUE, compiler
support is disabled.
|
Details
The parallel package from R 2.14.0 and later provides functions for
parallel execution of R code on machines with multiple cores or processors
or multiple computers. It is essentially a blend of the snow and
multicore packages. By default, the doParallel package uses
snow-like functionality. The snow-like functionality
should work fine on Unix-like systems, but the multicore-like
functionality is limited to a single sequential worker on Windows systems.
On workstations with multiple cores running Unix-like operating systems,
the system fork call is used to spawn copies of the current process.
The doParallel backend supports both multicore and snow options passed
through the foreach function.
The supported multicore options are preschedule, set.seed,
silent, and cores, which are analogous to the similarly named
arguments to mclapply, and are passed using the
.options.multicore argument to foreach. The supported snow options are
preschedule, which like its multicore analog can be used to chunk the
tasks so that each worker gets a prescheduled chunk of tasks, and
attachExportEnv, which can be used to attach the export environment
in certain cases where R's lexical scoping is unable to find a needed
export. The snow options are passed to foreach using the .options.snow
argument.
The function stopImplicitCluster can be used in vignettes and other places
where it is important to explicitly close the implicitly created cluster.
Examples
cl <- makePSOCKcluster(2)
registerDoParallel(cl)
m <- matrix(rnorm(9), 3, 3)
foreach(i=1:nrow(m), .combine=rbind)
stopCluster(cl)