doRNG 1.5.3

Registering doRNG for Persistent Reproducible Parallel Foreach Loops

Usage

registerDoRNG(seed = NULL, once = TRUE)

Arguments

seed
a numerical seed to use (as a single or 6-length numerical value)
once
a logical to indicate if the RNG sequence should be seeded at the beginning of each loop or only at the first loop.

Description

registerDoRNG registers the doRNG foreach backend. Subsequent %dopar% loops are then performed using the previously registered foreach backend, but are internally performed as %dorng% loops, making them fully reproducible.

Details

Briefly, the RNG is set, before each iteration, with seeds for L'Ecuyer's CMRG that overall generate a reproducible sequence of statistically independent random streams.

Note that (re-)registering a foreach backend other than doRNG, after a call to registerDoRNG disables doRNG -- which then needs to be registered.

Examples

library(doParallel)

cl <- makeCluster(2)

registerDoParallel(cl)

# One can make reproducible loops using the %dorng% operator
r1 <- foreach(i=1:4, .options.RNG=1234) %dorng% { runif(1) }

# or convert %dopar% loops using registerDoRNG
registerDoRNG(1234)

r2 <- foreach(i=1:4) %dopar% { runif(1) }

identical(r1, r2)



[1] TRUE

stopCluster(cl)

# Registering another foreach backend disables doRNG
cl <- makeCluster(3)

registerDoParallel(cl)

set.seed(1234)

s1 <- foreach(i=1:4) %dopar% { runif(1) }

set.seed(1234)

s2 <- foreach(i=1:4) %dopar% { runif(1) }

identical(s1, s2)



[1] FALSE

# doRNG is re-nabled by re-registering it
registerDoRNG()

set.seed(1234)

r3 <- foreach(i=1:4) %dopar% { runif(1) }

identical(r2, r3)



[1] TRUE

# NB: the results are identical independently of the task scheduling
# (r2 used 2 nodes, while r3 used 3 nodes)
# argument `once=FALSE` reseeds doRNG's seed at the beginning of each loop
registerDoRNG(1234, once=FALSE)

r1 <- foreach(i=1:4) %dopar% { runif(1) }

r2 <- foreach(i=1:4) %dopar% { runif(1) }

identical(r1, r2)



[1] TRUE

# Once doRNG is registered the seed can also be passed as an option to %dopar%
r1.2 <- foreach(i=1:4, .options.RNG=456) %dopar% { runif(1) }

r2.2 <- foreach(i=1:4, .options.RNG=456) %dopar% { runif(1) }

identical(r1.2, r2.2) && !identical(r1.2, r1)



[1] TRUE

stopCluster(cl)

See also

%dorng%