availableCores {parallelly} | R Documentation |
Get Number of Available Cores on The 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 = getOption2("parallelly.availableCores.methods", c("system", "cgroups.cpuset",
"cgroups.cpuquota", "cgroups2.cpu.max", "nproc", "mc.cores", "BiocParallel",
"_R_CHECK_LIMIT_CORES_", "Bioconductor", "LSF", "PJM", "PBS", "SGE", "Slurm",
"fallback", "custom")),
na.rm = TRUE,
logical = getOption2("parallelly.availableCores.logical", TRUE),
default = c(current = 1L),
which = c("min", "max", "all"),
omit = getOption2("parallelly.availableCores.omit", 0L)
)
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 |
methods |
A character vector specifying how to infer the number of available cores. |
na.rm |
If TRUE, only non-missing settings are considered/returned. |
logical |
Passed to
|
default |
The default number of cores to return if no non-missing settings are available. |
which |
A character specifying which settings to return.
If |
omit |
(integer; non-negative) Number of cores to not include. |
Details
The following settings ("methods") for inferring the number of cores are supported:
-
"system"
- QuerydetectCores(logical = logical)
. -
"cgroups.cpuset"
- On Unix, query control group (cgroup) valuecpuset.set
. -
"cgroups.cpuquota"
- On Unix, query control group (cgroup) valuecpu.cfs_quota_us
/cpu.cfs_period_us
. -
"cgroups2.cpu.max"
- On Unix, query control group (cgroup v2) valuescpu.max
. -
"nproc"
- On Unix, query system commandnproc
. -
"mc.cores"
- If available, returns the value of optionmc.cores
. Note thatmc.cores
is defined as the number of additional R processes that can be used in addition to the main R process. This means that withmc.cores = 0
all calculations should be done in the main R process, i.e. we have exactly one core available for our calculations. Themc.cores
option defaults to environment variable MC_CORES (and is set accordingly when the parallel package is loaded). Themc.cores
option is used by for instancemclapply()
of the parallel package. -
"connections"
- Query the current number of available R connections perfreeConnections()
. This is the maximum number of socket-based parallel cluster nodes that are possible launch, because each one needs its own R connection. The exception is whenfreeConnections()
is zero, then1L
is still returned, becauseavailableCores()
should always return a positive integer. -
"BiocParallel"
- Query environment variable BIOCPARALLEL_WORKER_NUMBER (integer), which is defined and used by BiocParallel (>= 1.27.2). If the former is set, this is the number of cores considered. -
"_R_CHECK_LIMIT_CORES_"
- Query environment variable _R_CHECK_LIMIT_CORES_ (logical or"warn"
) used byR CMD check
and set to true byR CMD check --as-cran
. If set to a non-false value, then a maximum of 2 cores is considered. -
"Bioconductor"
- Query environment variable IS_BIOC_BUILD_MACHINE (logical) used by the Bioconductor (>= 3.16) build and check system. If set to true, then a maximum of 4 cores is considered. -
"LSF"
- Query Platform Load Sharing Facility (LSF) environment variable LSB_DJOB_NUMPROC. Jobs with multiple (CPU) slots can be submitted on LSF usingbsub -n 2 -R "span[hosts=1]" < hello.sh
. -
"PJM"
- Query Fujitsu Technical Computing Suite (that we choose to shorten as "PJM") environment variables PJM_VNODE_CORE and PJM_PROC_BY_NODE. The first is set when submitted withpjsub -L vnode-core=8 hello.sh
. -
"PBS"
- Query TORQUE/PBS environment variables PBS_NUM_PPN and NCPUS. Depending on PBS system configuration, these resource parameters may or may not default to one. An example of a job submission that results in this isqsub -l nodes=1:ppn=2
, which requests one node with two cores. -
"SGE"
- Query Sun Grid Engine/Oracle Grid Engine/Son of Grid Engine (SGE) and Univa Grid Engine (UGE) environment variable NSLOTS. An example of a job submission that results in this isqsub -pe smp 2
(orqsub -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. If SLURM_CPUS_PER_TASK is not set, then it will fall back to use SLURM_CPUS_ON_NODE if the job is a single-node job (SLURM_JOB_NUM_NODES is 1), e.g.sbatch --ntasks=2 hello.sh
. To make sure all tasks are assign to a single node, specify--nodes=1
, e.g.sbatch --nodes=1 --ntasks=16 hello.sh
. -
"custom"
- If optionparallelly.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. It is safe for this custom function to callavailableCores()
; if done, the custom function will not be recursively called.
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.
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.
Avoid ending up with zero cores
Note that some machines might have a limited number of cores, or the R process runs in a container or a cgroup that only provides a small number of cores. In such cases:
ncores <- availableCores() - 1
may return zero, which is often not intended and is likely to give an error downstream. Instead, use:
ncores <- availableCores(omit = 1)
to put aside one of the cores from being used. Regardless how many cores you put aside, this function is guaranteed to return at least one core.
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(parallelly.availableCores.methods = "mc.cores")
and
then the number of cores to use, e.g. options(mc.cores = 8)
.
See Also
To get the set of available workers regardless of machine,
see availableWorkers()
.
Examples
message(paste("Number of cores available:", availableCores()))
## Not run:
options(mc.cores = 2L)
message(paste("Number of cores available:", availableCores()))
## End(Not run)
## Not run:
## IMPORTANT: availableCores() may return 1L
options(mc.cores = 1L)
ncores <- availableCores() - 1 ## ncores = 0
ncores <- availableCores(omit = 1) ## ncores = 1
message(paste("Number of cores to use:", ncores))
## End(Not run)
## Not run:
## Use 75% of the cores on the system but never more than four
options(parallelly.availableCores.custom = function() {
ncores <- max(parallel::detectCores(), 1L, na.rm = TRUE)
ncores <- min(as.integer(0.75 * ncores), 4L)
max(1L, ncores)
})
message(paste("Number of cores available:", availableCores()))
## Use 50% of the cores according to availableCores(), e.g.
## allocated by a job scheduler or cgroups.
## Note that it is safe to call availableCores() here.
options(parallelly.availableCores.custom = function() {
0.50 * parallelly::availableCores()
})
message(paste("Number of cores available:", availableCores()))
## End(Not run)