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p <- mcparallel(1:10)

p <- mcparallel(1:10)

q <- mcparallel(1:20)

q <- mcparallel(1:20)

# wait for both jobs to finish and collect all results

# wait for both jobs to finish and collect all results

res <- mccollect(list(p, q))

res <- mccollect(list(p, q))

p <- mcparallel(1:10)

p <- mcparallel(1:10)

mccollect(p, wait = FALSE, 10) # will retrieve the result (since it's fast)

mccollect(p, wait = FALSE, 10) # will retrieve the result (since it's fast)

mccollect(p, wait = FALSE)     # will signal the job as terminating

mccollect(p, wait = FALSE)     # will signal the job as terminating

mccollect(p, wait = FALSE)     # there is no longer such a job

mccollect(p, wait = FALSE)     # there is no longer such a job

\dontshow{set.seed(123, "L'Ecuyer"); mc.reset.stream()}

\dontshow{set.seed(123, "L'Ecuyer"); mc.reset.stream()}

# a naive parallel lapply can be created using mcparallel alone:

# a naive parallel lapply can be created using mcparallel alone:

jobs <- lapply(1:10, function(x) mcparallel(rnorm(x), name = x))

jobs <- lapply(1:10, function(x) mcparallel(rnorm(x), name = x))

mccollect(jobs)

mccollect(jobs)

}

}