(Parallel) Random number seed question...
On Mon, 16 Nov 2009, Blair Christian wrote:
Hi All, I have k identical parallel pieces of code running, each using n.rand random numbers.? I would like to use the same RNG (for now), and set the seeds so that I can guarantee that there are no overlaps in the random numbers sampled by the k pieces of code.? Another side goal is to have reproducibility of my results.? In?the past I have used C with SPRNG for this task, but I'm hoping that there is an easy way to do this in R with poor man's parallelization (eg running multiple Rs on multiple processors without the overhead of setting up any mpi or using snow(fall)). It is not clear from the documentation if set.seed arguments are sequential or not for a given RNG, eg if set.seed(1) on processor 1, set.seed(1+n.rand) on processor 2, set.seed(1+2*n.rand) on processor 3, etc for the default RNG "Mersenne-Twister". An easy approach would be to simply write a script to generate n.rand numbers, records the .Random.seed and proceeds in that manner- inelegant, but effective. My question here is "Is there a better way?" (mvtnorm part directed to Torsten Hothorn) To further clarify, it seems there is a different RNG for normal (rnorm) than for everything else? (eg RNGKind( .., normal.kind="Inversion"); further, does anybody know if mvtnorm uses this generator?
mvtnorm is based on FORTRAN code which uses unif_rand() from the C API:
void F77_SUB(rndstart)(void) { GetRNGstate(); }
void F77_SUB(rndend)(void) { PutRNGstate(); }
double F77_SUB(unifrnd)(void) { return unif_rand(); }
Torsten
Further, some RNGs seem to be based on the archictecture (eg the Knuth-TAOCP-2002 for example)- is the period really related to 2^32, or is it dependent the architecture, 2^64 for 64 bit R and 2^32 for 32 bit R? I noticed there are several packages related to RNG- please direct me to a vignette/R news article/previous post if this has been covered ad nauseum. I have skimmed vignettes/docs for rsprng package, RNG doc in base, setRNG package, mvtnorm package vignette (Or am I setting myself up to write a current RNG doc?) (directed to Gregory Warnes) I found a presentation by Gregory Warnes from 1999 addressing these same questions (and uses a "collings generator" in some C code). http://www.r-project.org/conferences/DSC-1999/slides/warnes.ps.gz Have you turned to the snowfall related parallel implementations, did your Collings generator work well, or have you discovered another trick you might like to share? Thank you all for your time and excellent contributions to the open source community, Blair