Define a parallel cluster object to be used in internal functions

This function defines a object that is placed in a relevant internal environment defined in mirt. Internal functions such as calcLogLik, fscores, etc, will utilize this object automatically to capitalize on parallel processing architecture. The object defined is a call from parallel::makeCluster(). Note that if you are defining other parallel objects (for simulation designs, for example) it is not recommended to define a mirtCluster.

Usage

mirtCluster(spec, omp_threads, remove = FALSE, ...)

Arguments

spec: input that is passed to parallel::makeCluster(). If no input is given the maximum number of available local cores minus 1 will be used. Setting this to NULL will skip a new definition (allows omp_threads to be used independently)
omp_threads: number of OpenMP threads to use (currently applies to E-step computations only). Not used when argument input is missing
remove: logical; remove previously defined mirtCluster()?
...: additional arguments to pass to parallel::makeCluster

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06

Author

Phil Chalmers rphilip.chalmers@gmail.com

Examples


if (FALSE) { # \dontrun{
if(interactive()){
  # use all available cores
  mirtCluster()
  mirtCluster(remove = TRUE)

  # make 4 cores available for parallel computing
  mirtCluster(4)
  mirtCluster(remove = TRUE)

  # create 3 core architecture in R, and 4 thread architecture with OpenMP
  mirtCluster(spec = 3, omp_threads = 4)

  # leave previous multicore objects, but change omp_threads
  mirtCluster(spec = NULL, omp_threads = 2)
}

} # }