R: ClusterFunctions for Parallel Multicore Execution

makeClusterFunctionsMulticore {batchtools} | R Documentation

## ClusterFunctions for Parallel Multicore Execution

### Description

Jobs are spawned asynchronously using the functions `mcparallel` and `mccollect` (both in parallel). Does not work on Windows, use `makeClusterFunctionsSocket` instead.

### Usage

    makeClusterFunctionsMulticore(ncpus = NA_integer_, fs.latency = 0)

### Arguments

`ncpus` | [`integer(1)`] Number of CPUs. Default is to use all logical cores. The total number of cores "available" can be set via the option `mc.cores` and defaults to the heuristic implemented in `detectCores`.
`fs.latency` | [`numeric(1)`] Expected maximum latency of the file system, in seconds. Set to a positive number for network file systems like NFS which enables more robust (but also more expensive) mechanisms to access files and directories. Usually safe to set to `0` to disable the heuristic, e.g. if you are working on a local file system.

### Value

[`ClusterFunctions`].

### See Also

Other ClusterFunctions: `makeClusterFunctionsDocker`, `makeClusterFunctionsInteractive`, `makeClusterFunctionsLSF`, `makeClusterFunctionsOpenLava`, `makeClusterFunctionsSGE`, `makeClusterFunctionsSSH`, `makeClusterFunctionsSlurm`, `makeClusterFunctionsSocket`, `makeClusterFunctionsTORQUE`, `makeClusterFunctions`

[Package batchtools version 0.9.11 Index]