Nothing
visualize <- FALSE # TRUE for manual tests with visualization of results
if(visualize)
{
library(parallel)
#fonction basique evaluant la moyenne empirique d'un echantillon gaussien
f <- function(i) mean(rnorm(1e4, mean=i))
#exemple simple
glist <- 1:20
cl <- parallel::makeCluster(2)
system.time(
res <- parallel::parLapply(cl, glist, f)
)
parallel::stopCluster(cl)
#exemple en faisant varier le nombre de coeurs et le nombre de simulations
nbsimu <- 10^(1:2)
cores <- 1:4
cores <- 1:getOption("cl.cores", 2)
partime <- matrix(NA, length(nbsimu), length(cores)+1)
colnames(partime) <- c("R", paste("core",cores))
rownames(partime) <- paste("n", nbsimu, sep="=")
partime[, 1] <- sapply(1:length(nbsimu), function(i)
system.time(lapply(1:nbsimu[i], f))[3])
for(j in 1:length(cores))
{
print(cores[j])
cl <- parallel::makeCluster(cores[j])
partime[, j+1] <- sapply(1:length(nbsimu), function(i)
system.time(parallel::parLapply(cl, 1:nbsimu[i], f))[3])
parallel::stopCluster(cl)
}
partime
}
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