Get Number of Available Cores on The Current Machine

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",
    "/proc/self/status", "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 constraints = "multicore" will force a single core to be reported. Using constraints = "connections", will append "connections" to the methods argument. It is possible to specify multiple constraints, e.g. constraints = c("connections", "multicore").
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 detectCores(logical = logical), which, if supported, returns the number of logical CPUs (TRUE) or physical CPUs/cores (FALSE). At least as of R 4.2.2, detectCores() this argument on Linux. This argument is only if argument methods includes "system".
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" (default), the minimum value is returned. If "max", the maximum value is returned (be careful!) If "all", all values are returned.
omit: (integer; non-negative) Number of cores to not include.

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.

Details

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

"system" - Query detectCores(logical = logical).
"/proc/self/status" - Query Cpus_allowed_list of /proc/self/status.
"cgroups.cpuset" - On Unix, query control group (cgroup v1) value cpuset.set.
"cgroups.cpuquota" - On Unix, query control group (cgroup v1) value cpu.cfs_quota_us / cpu.cfs_period_us.
"cgroups2.cpu.max" - On Unix, query control group (cgroup v2) values cpu.max.
"nproc" - On Unix, query system command nproc.
"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() of the parallel package.
"connections" - Query the current number of available R connections per freeConnections(). 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 when freeConnections() is zero, then 1L is still returned, because availableCores() 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 by R CMD check and set to true by R 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)/OpenLava environment variable LSB_DJOB_NUMPROC. Jobs with multiple (CPU) slots can be submitted on LSF using bsub -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 with pjsub -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 is qsub -l nodes=1:ppn=2, which requests one node with two cores.
"SGE" - Query the "Grid Engine" scheduler 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. Known Grid Engine schedulers are Oracle Grid Engine (OGE; acquired Sun Microsystems in 2010), Univa Grid Engine (UGE; fork of open-source SGE 6.2u5), Altair Grid Engine (AGE; acquires Univa Corporation in 2020), Son of Grid Engine (SGE aka SoGE; open-source fork of SGE 6.2u5), and
"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 option parallelly.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 call availableCores(); 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.

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).

Examples

message(paste("Number of cores available:", availableCores()))
#> Number of cores available: 8

if (FALSE) { # \dontrun{
options(mc.cores = 2L)
message(paste("Number of cores available:", availableCores()))
} # }

if (FALSE) { # \dontrun{
## 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))
} # }

if (FALSE) { # \dontrun{
## 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()))
} # }