makeClusterMPI

The number workers (as a positive integer).

workers

Optional arguments passed to
<code><a rd-options="parallel:makeCluster" href="/link/makeCluster?package=future&version=1.19.1&to=parallel%3AmakeCluster" data-mini-rdoc="parallel:makeCluster::makeCluster">makeCluster</a>(workers, type = "MPI", ...)</code>.

&#8230;

If TRUE, the cluster will be automatically stopped
(using <code><a rd-options="parallel:makeCluster" href="/link/stopCluster?package=future&version=1.19.1&to=parallel%3AmakeCluster" data-mini-rdoc="parallel:makeCluster::stopCluster">stopCluster</a>()</code>) when it is
garbage collected, unless already stopped.

autoStop

If TRUE, informative messages are outputted.

verbose

The <code>makeClusterMPI()</code> function creates an MPI cluster of R workers
for parallel processing. This function utilizes
<code>makeCluster(..., type = "MPI")</code> of the parallel package and
tweaks the cluster in an attempt to avoid
<code><a rd-options="parallel:makeCluster" href="/link/stopCluster()?package=future&version=1.19.1&to=parallel%3AmakeCluster" data-mini-rdoc="parallel:makeCluster::stopCluster()">stopCluster()</a></code> from hanging (1).
WARNING: This function is very much in a beta version and should
only be used if <code>parallel::makeCluster(..., type = "MPI")</code> fails.

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

makeClusterMPI function

Optional arguments passed to
<code><a rd-options='parallel:makeCluster' href='makeCluster'>makeCluster</a>(workers, type = "MPI", ...)</code>.

If TRUE, the cluster will be automatically stopped
(using <code><a rd-options='parallel:makeCluster' href='stopCluster'>stopCluster</a>()</code>) when it is
garbage collected, unless already stopped.

The <code>makeClusterMPI()</code> function creates an MPI cluster of R workers
for parallel processing. This function utilizes
<code>makeCluster(..., type = "MPI")</code> of the parallel package and
tweaks the cluster in an attempt to avoid
<code><a rd-options='parallel:makeCluster' href='stopCluster()'>stopCluster()</a></code> from hanging (1).
WARNING: This function is very much in a beta version and should
only be used if <code>parallel::makeCluster(..., type = "MPI")</code> fails.

makeClusterMPI: Create a Message Passing Interface (MPI) cluster of R workers for parallel processing

Description

Usage

Arguments

Value

Details

References

See Also