future (version 1.0.1)

multicore: Create a multicore future whose value will be resolved asynchroneously 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(expr, envir = parent.frame(), substitute = TRUE, globals = TRUE, workers = availableCores(constraints = "multicore"), gc = FALSE, earlySignal = FALSE, ...)

Arguments

expr

An R expression.

envir

The environment in which the evaluation is done and from which globals are obtained.

substitute

If TRUE, argument expr is substitute():ed, otherwise not.

globals

If TRUE, global objects are validated at the point in time when the future is created (always before it is resolved), that is, they identified and located. If some globals fail to be located, an informative error is generated.

workers

The maximum number of multicore futures that can be active at the same time before blocking.

gc

If TRUE, the garbage collector run after the future is resolved (in the process that evaluated the future).

earlySignal

Specified whether conditions should be signaled as soon as possible or not.

...

Not used.

Value

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

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 systems support multicore futures. For instance, it is not supported on Microsoft Windows. Trying to create multicore futures on non-supported systems will silently fall back to using eager futures, which effectively corresponds to a multicore future that can handle one parallel process (the current one) before blocking.

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 %<=%< a=""> will create multicore futures.

See Also

For processing in multiple background R sessions, see multisession futures. For multicore processing with fallback to multisession where the former is not supported, see multiprocess futures.

Use availableCores() to see the total number of cores that are available for the current R session. Use availableCores("multicore") > 1L to check whether multicore futures are supported or not on the current system.

Examples

## Use multicore futures
plan(multicore)

## A global variable
a <- 0

## Create multicore 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)