Internal function to enable (a)synchronous parallel processing

This function checks if parallel processing can be set up and enables it. Ideally this is done by the user for more control! In the package parallelization is usually only used for predictions and projections, but not for inference in which case parallel inference should be handled by the engine.

Usage

ibis_future(
  plan_exists = FALSE,
  cores = getOption("ibis.nthread", default = 2),
  strategy = getOption("ibis.futurestrategy"),
  workers = NULL
)

Arguments

plan_exists: A logical check on whether an existing future plan exists (Default: FALSE).
cores: A numeric number stating the number of cores to use.
strategy: A character denoting the strategy to be used for future. See help of future for options. (Default: "multisession").
workers: An optional list of remote machines or workers, e.g. "c(remote.server.org)". Alternatively a "cluster" object can be provided.

Value

Invisible

Details

Currently supported strategies are:

"sequential" = Resolves futures sequentially in the current R process (Package default).
"multisession" = Resolves futures asynchronously across 'cores' sessions.
"multicore" = Resolves futures asynchronously across on forked processes. Only works on UNIX systems!
"cluster" = Resolves futures asynchronously in sessions on this or more machines.
"slurm" = To be implemented: Slurm linkage via batchtools.

Note

The 'plan' set by future exists after the function has been executed.

If the aim is to parallize across many species, this is better done in a scripted solution. Make sure not to parallize predictions within existing clusters to avoid out-of-memory issues.

Examples

if (FALSE) { # \dontrun{
# Starts future job. F in this case is a prediction function.
ibis_future(cores = 4, strategy = "multisession")
} # }