The current/main R session counts as one, meaning the minimum number of cores available is always at least one.
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"))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.
A character vector specifying how to infer the number of available cores.
If TRUE, only non-missing settings are considered/returned.
The default number of cores to return if no non-missing settings are available.
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.
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.
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).
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.
To get the number of available workers regardless of machine,
see availableWorkers().