Check If Forked Processing ("multicore") is Supported

Certain parallelization methods in R rely on forked processing, e.g. parallel::mclapply(), parallel::makeCluster(n, type = "FORK"), doMC::registerDoMC(), and future::plan("multicore"). Process forking is done by the operating system and support for it in R is restricted to Unix-like operating systems such as Linux, Solaris, and macOS. R running on Microsoft Windows does not support forked processing. In R, forked processing is often referred to as "multicore" processing, which stems from the 'mc' of the mclapply() family of functions, which originally was in a package named multicore which later was incorporated into the parallel package. This function checks whether or not forked (aka "multicore") processing is supported in the current R session.

Usage

supportsMulticore(...)

Arguments

...

Internal usage only.

Value

TRUE if forked processing is supported and not disabled, otherwise FALSE.

Support for process forking

While R supports forked processing on Unix-like operating system such as Linux and macOS, it does not on the Microsoft Windows operating system.

For some R environments it is considered unstable to perform parallel processing based on forking. This is for example the case when using RStudio, cf. RStudio Inc. recommends against using forked processing when running R from within the RStudio software. This function detects when running in such an environment and returns FALSE, despite the underlying operating system supports forked processing. A warning will also be produced informing the user about this the first time time this function is called in an R session. This warning can be disabled by setting R option parallelly.supportsMulticore.unstable, or environment variable R_PARALLELLY_SUPPORTSMULTICORE_UNSTABLE to "quiet".

Enable or disable forked processing

It is possible to disable forked processing for futures by setting R option parallelly.fork.enable to FALSE. Alternatively, one can set environment variable R_PARALLELLY_FORK_ENABLE to false. Analogously, it is possible to override disabled forking by setting one of these to TRUE.

Why not forked processing?

One reason for not using forked parallel processing in R is that is not guaranteed to be stable in all environments or in all contexts, which also depends on which functions are called in the forked processes. Here is what R Core developer of the parallel::mclapply() family of functions said on R-devel (2020-04-29):

"Do NOT use mcparallel() in packages except as a non-default option that user can set ... Multicore is intended for HPC applications that need to use many cores for computing-heavy jobs, but it does not play well with RStudio and more importantly you [as the developer] don't know the resource available so only the user can tell you when it's safe to use."

Examples

## Check whether or not forked processing is supported
supportsMulticore()
#> [1] TRUE