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future (version 1.15.1)

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",
    "_R_CHECK_LIMIT_CORES_", "PBS", "SGE", "Slurm", "fallback", "custom")),
  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") and then the number of cores to use, e.g. options(mc.cores = 8). 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 = 8).

Details

The following settings ("methods") for inferring the number of cores are supported:

  • "system" - Query detectCores().

  • "mc.cores" - If available, returns the value of option mc.cores. 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 variables PBS_NUM_PPN and NCPUS. Depending on PBS system configuration, these 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.

  • "custom" - If option future.availableCores.custom is set and a function, then this function will be called (without arguments) and it's value will be coerced to an integer, which will be interpreted as a number of available cores. If the value is NA, then it will be ignored.

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().