future: multicore – R documentation

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multicore

Create a multicore future whose value will be resolved asynchronously in a forked parallel process

Description

A multicore future is a future that uses multicore evaluation, which means that its value is computed and resolved in parallel in another process.

Usage

multicore(
  ...,
  workers = availableCores(constraints = "multicore"),
  envir = parent.frame()
)

Arguments

`...`	Additional arguments passed to `Future()`.
`workers`	A positive numeric scalar or a function specifying the maximum number of parallel futures that can be active at the same time before blocking. If a function, it is called without arguments when the future is created and its value is used to configure the workers. The function should return a numeric scalar.
`envir`	The environment from where global objects should be identified.

Details

This function will block if all cores are occupied and will be unblocked as soon as one of the already running multicore futures is resolved. For the total number of cores available including the current/main R process, see availableCores().

Not all operating systems support process forking and thereby not multicore futures. For instance, forking is not supported on Microsoft Windows. Moreover, process forking may break some R environments such as RStudio. Because of this, the future package disables process forking also in such cases. See supportsMulticore() for details. Trying to create multicore futures on non-supported systems or when forking is disabled will result in multicore futures falling back to becoming sequential futures.

The preferred way to create an multicore future is not to call this function directly, but to register it via plan(multicore) such that it becomes the default mechanism for all futures. After this future() and %<-% will create multicore futures.

Value

A MulticoreFuture If workers == 1, then all processing using done in the current/main R session and we therefore fall back to using an sequential future. This is also the case whenever multicore processing is not supported, e.g. on Windows.

Examples

## Use multicore futures
plan(multicore)

## A global variable
a <- 0

## Create future (explicitly)
f <- future({
  b <- 3
  c <- 2
  a * b * c
})

## A multicore future is evaluated in a separate forked
## process.  Changing the value of a global variable
## will not affect the result of the future.
a <- 7
print(a)

v <- value(f)
print(v)
stopifnot(v == 0)

future

Unified Parallel and Distributed Processing in R for Everyone

v1.21.0

LGPL (>= 2.1)

Authors

Henrik Bengtsson [aut, cre, cph]

Initial release