future (version 1.3.0)

availableCores: Get number of available cores on current machine

Description

The current/main R session counts as one, meaning the minimum number of cores available is always at least one.

Usage

availableCores(constraints = NULL,
  methods = getOption("future.availableCores.methods", c("system",
  "mc.cores+1", "_R_CHECK_LIMIT_CORES_", "PBS", "SGE", "Slurm", "fallback")),
  na.rm = TRUE, default = c(current = 1L), which = c("min", "max", "all"))

Arguments

constraints
An optional character specifying under what constraints ("purposes") we are requesting the values. For instance, on systems where multicore processing is not supported (i.e. Windows), using constrains="multicore" will force a single core to be reported.
methods
A character vector specifying how to infer the number of available cores.
na.rm
If TRUE, only non-missing settings are considered/returned.
default
The default number of cores to return if no non-missing settings are available.
which
A character specifying which settings to return. If "min", the minimum value is returned. If "max", the maximum value is returned (be careful!) If "all", all values are returned.

Value

Return a positive (>=1) integer. If which="all", then more than one value may be returned. Together with na.rm=FALSE missing values may also be returned.

Advanced usage

It is possible to override the maximum number of cores on the machine as reported by availableCores(methods="system"). This can be done by first specifying options(future.availableCores.methods="mc.cores+1") and then the number of cores to use (in addition to the main R process), e.g. options(mc.cores=8) will cause the value of availableCores() to be 9 (=8+1). Having said this, it is almost always better to do this by explicitly setting the number of workers when specifying the future strategy, e.g. plan(multiprocess, workers=9).

Details

The following settings ("methods") for inferring the number of cores are supported:
  • "system" - Query detectCores().
  • "mc.cores+1" - If available, returns the value of option mc.cores + 1. Note that mc.cores is defined as the number of additional R processes that can be used in addition to the main R process. This means that with mc.cores=0 all calculations should be done in the main R process, i.e. we have exactly one core available for our calculations. The mc.cores option defaults to environment variable MC_CORES (and is set accordingly when the parallel package is loaded). The mc.cores option is used by for instance mclapply().
  • "PBS" - Query TORQUE/PBS environment variable PBS_NUM_PPN. Depending on PBS system configuration, this resource parameter may or may not default to one. An example of a job submission that results in this is qsub -l nodes=1:ppn=2, which requests one node with two cores.
  • "SGE" - Query Sun/Oracle Grid Engine (SGE) environment variable NSLOTS. An example of a job submission that results in this is qsub -pe smp 2 (or qsub -pe by_node 2), which requests two cores on a single machine.
  • "Slurm" - Query Simple Linux Utility for Resource Management (Slurm) environment variable SLURM_CPUS_PER_TASK. This may or may not be set. It can be set when submitting a job, e.g. sbatch --cpus-per-task=2 hello.sh or by adding #SBATCH --cpus-per-task=2 to the `hello.sh` script.
For any other value of a methods element, the R option with the same name is queried. If that is not set, the system environment variable is queried. If neither is set, a missing value is returned.

See Also

To get the number of available workers regardless of machine, see availableWorkers().