MulticoreFuture-class

MulticoreFuture

An R <a rd-options="base" href="/link/expression?package=future&version=1.10.0&to=base" data-mini-rdoc="base::expression">expression</a>.

expr

The <a rd-options="" href="/link/environment?package=future&version=1.10.0" data-mini-rdoc="future::environment">environment</a> from where global objects should be
identified.

envir

If TRUE, argument <code>expr</code> is
<code><a rd-options="base" href="/link/substitute?package=future&version=1.10.0&to=base" data-mini-rdoc="base::substitute">substitute</a>()</code>:ed, otherwise not.

substitute

(optional) a logical, a character vector, or a named list
to control how globals are handled.
For details, see section 'Globals used by future expressions'
in the help for <code><a rd-options="" href="/link/future?package=future&version=1.10.0" data-mini-rdoc="future::future">future</a>()</code>.

globals

Additional named elements passed to <code><a rd-options="" href="/link/Future?package=future&version=1.10.0" data-mini-rdoc="future::Future">Future</a>()</code>.

An multicore future is a future whose value will be resolved asynchronously in a parallel process

internal

The purpose of this package is to provide a lightweight and
unified Future API for sequential and parallel processing of R
expression via futures. The simplest way to evaluate an expression
in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`.
This package implements sequential, multicore, multisession, and
cluster futures. With these, R expressions can be evaluated on the
local machine, in parallel a set of local machines, or distributed
on a mix of local and remote machines.
Extensions to this package implement additional backends for
processing futures via compute cluster schedulers etc.
Because of its unified API, there is no need to modify any code in order
switch from sequential on the local machine to, say, distributed
processing on a remote compute cluster.
Another strength of this package is that global variables and functions
are automatically identified and exported as needed, making it
straightforward to tweak existing code to make use of futures.

Henrik Bengtsson

future

Unified Parallel and Distributed Processing in R for Everyone

MulticoreFuture-class function

An R <a rd-options='base' href='expression'>expression</a>.

The <a rd-options='' href='environment'>environment</a> from where global objects should be
identified.

If TRUE, argument <code>expr</code> is
<code><a rd-options='base' href='substitute'>substitute</a>()</code>:ed, otherwise not.

(optional) a logical, a character vector, or a named list
to control how globals are handled.
For details, see section 'Globals used by future expressions'
in the help for <code><a rd-options='' href='future'>future</a>()</code>.

Additional named elements passed to <code><a rd-options='' href='Future'>Future</a>()</code>.

MulticoreFuture-class: An multicore future is a future whose value will be resolved asynchronously in a parallel process

Description

Usage

Arguments

Value

See Also