inst/doc/Parallel-computing.R

In SimDesign: Structure for Organizing Monte Carlo Simulation Designs

## ----nomessages, echo = FALSE-------------------------------------------------
knitr::opts_chunk$set(
  warning = FALSE,
  message = FALSE,
  fig.height = 5,
  fig.width = 5
)
options(digits=4)
par(mar=c(3,3,1,1)+.1)

## ----eval=FALSE---------------------------------------------------------------
# library(parallel)
# primary <- '192.168.2.1'
# IPs <- list(list(host=primary, user='myname', ncore=8), list(host='192.168.2.2', user='myname', ncore=6))
# spec <- lapply(IPs, function(IP) rep(list(list(host=IP$host, user=IP$user)), IP$ncore))
# spec <- unlist(spec, recursive=FALSE)
# cl <- makeCluster(master=primary, spec=spec, type = 'PSOCK')
# Final <- runSimulation(..., cl=cl)
# stopCluster(cl)

## ----eval=FALSE---------------------------------------------------------------
# library(parallel)
# primary <- 'master'
# IPs <- list(list(host=primary, ncore=8), list(host='slave', ncore=6))
# spec <- lapply(IPs, function(IP) rep(list(list(host=IP$host)), IP$ncore))
# spec <- unlist(spec, recursive=FALSE)
# cl <- makeCluster(master=primary, spec=spec, type = 'PSOCK')
# Final <- runSimulation(..., cl=cl)
# stopCluster(cl)

## ----eval=FALSE---------------------------------------------------------------
# library(future)
# plan(multisession, workers = 2)
# 
# res <- runSimulation(design=Design, replications=1000, generate=Generate,
#                      analyse=Analyse, summarise=Summarise,
#                      parallel = 'future')

## ----eval=FALSE---------------------------------------------------------------
# library(progressr)
# 
# # Rstudio style handler (if using RStudio)
# handlers("rstudio")
# 
# # or using the cli package for terminal-based progress
# handlers('cli')
# 
# # See help(progressr) for additional options and details
# 
# # to use progressr, wrap/pipe inside with_progress()
# res <- with_progress(runSimulation(design=Design, replications=1000, generate=Generate,
#                      analyse=Analyse, summarise=Summarise,
#                      parallel = 'future'))

## ----eval=FALSE---------------------------------------------------------------
# plan(sequential) # release workers