Type:	Package
Title:	Parallel Programming Tools for 'Rcpp'
Version:	5.1.10
Description:	High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.
Depends:	R (≥ 3.0.2)
Suggests:	Rcpp, RUnit, knitr, rmarkdown
SystemRequirements:	GNU make, Intel TBB, Windows: cmd.exe and cscript.exe, Solaris: g++ is required
License:	GPL (≥ 3)
URL:	https://rcppcore.github.io/RcppParallel/, https://github.com/RcppCore/RcppParallel
BugReports:	https://github.com/RcppCore/RcppParallel/issues
Biarch:	TRUE
RoxygenNote:	7.1.1
Encoding:	UTF-8
NeedsCompilation:	yes
Packaged:	2025-01-23 23:26:25 UTC; kevin
Author:	JJ Allaire [aut], Romain Francois [aut, cph], Kevin Ushey [aut, cre], Gregory Vandenbrouck [aut], Marcus Geelnard [aut, cph] (TinyThread library, https://tinythreadpp.bitsnbites.eu/), Hamada S. Badr [ctb], Posit, PBC [cph], Intel [aut, cph] (Intel TBB library, https://www.threadingbuildingblocks.org/), Microsoft [cph]
Maintainer:	Kevin Ushey <kevin@rstudio.com>
Repository:	CRAN
Date/Publication:	2025-01-24 02:00:02 UTC

Parallel programming tools for Rcpp

Description

High level functions for doing parallel programming with Rcpp. For example, the parallelFor() function can be used to convert the work of a standard serial "for" loop into a parallel one, and the parallelReduce() function can be used for accumulating aggregate or other values.

Details

The high level interface enables safe and robust parallel programming without direct manipulation of operating system threads. On Windows, macOS, and Linux systems the underlying implementation is based on Intel TBB (Threading Building Blocks). On other platforms, a less-performant fallback implementation based on the TinyThread library is used.

For additional documentation, see the package website at:

https://rcppcore.github.io/RcppParallel/

Create a skeleton for a new package depending on RcppParallel

Description

RcppParallel.package.skeleton automates the creation of a new source package that intends to use features of RcppParallel.

Usage

RcppParallel.package.skeleton(name = "anRpackage", example_code = TRUE, ...)

Arguments

Details

It is based on the package.skeleton function which it executes first.

In addition to Rcpp.package.skeleton :

The ‘⁠DESCRIPTION⁠’ file gains an Imports line requesting that the package depends on RcppParallel and a LinkingTo line so that the package finds RcppParallel header files.

The ‘⁠NAMESPACE⁠’ gains a useDynLib directive as well as an importFrom(RcppParallel, evalCpp to ensure instantiation of RcppParallel.

The ‘⁠src⁠’ directory is created if it does not exists and a ‘⁠Makevars⁠’ file is added setting the environment variables ‘⁠PKG_LIBS⁠’ to accomodate the necessary flags to link with the RcppParallel library.

If the example_code argument is set to TRUE, example files ‘⁠vector-sum.cpp⁠’ is created in the ‘⁠src⁠’ directory. Rcpp::compileAttributes() is then called to generate src/RcppExports.cpp and R/RcppExports.R. These files are given as an example and should eventually by removed from the generated package.

Value

Nothing, used for its side effects

References

Read the Writing R Extensions manual for more details.

Once you have created a source package you need to install it: see the R Installation and Administration manual, INSTALL and install.packages.

See Also

package.skeleton

Examples

## Not run: 
# simple package
RcppParallel.package.skeleton("foobar")

## End(Not run)

Compilation flags for RcppParallel

Description

Output the compiler or linker flags required to build against RcppParallel.

Usage

CxxFlags()

LdFlags()

RcppParallelLibs()

Details

These functions are typically called from Makevars as follows:

PKG_LIBS += $(shell "${R_HOME}/bin/Rscript" -e "RcppParallel::LdFlags()")

On Windows, the flags ensure that the package links with the built-in TBB library. On Linux and macOS, the output is empty, because TBB is loaded dynamically on load by RcppParallel.

R packages using RcppParallel should also add the following to their NAMESPACE file:

importFrom(RcppParallel, RcppParallelLibs)

This is necessary to ensure that RcppParallel (and so, TBB) is loaded and available.

Value

Returns NULL, invisibly. These functions are called for their side effects (writing the associated flags to stdout).

Thread options for RcppParallel

Description

Set thread options (number of threads to use for task scheduling and stack size per-thread) for RcppParallel.

Usage

setThreadOptions(numThreads = "auto", stackSize = "auto")

defaultNumThreads()

Arguments

Details

RcppParallel is automatically initialized with the default number of threads and thread stack size when it loads. You can call setThreadOptions() at any time to change the defaults.

The parallelFor() and parallelReduce() also accept numThreads as an argument, if you'd like to control the number of threads specifically to be made available for a particular parallel function call. Note that this value is advisory, and TBB may choose a smaller number of threads if the number of requested threads cannot be honored on the system.

Value

defaultNumThreads() returns the default number of threads used by RcppParallel, if another value isn't specified either via setThreadOptions() or explicitly in calls to parallelFor() and parallelReduce().

Examples

## Not run: 
library(RcppParallel)
setThreadOptions(numThreads = 4)
defaultNumThreads()

## End(Not run)

Get the Path to a TBB Library

Description

Retrieve the path to a TBB library. This can be useful for R packages using RcppParallel that wish to use, or re-use, the version of TBB that RcppParallel has been configured to use.

Usage

tbbLibraryPath(name = NULL)

Arguments