portable parallel seeds project: request for critiques

I've got another edition of my simulation replication framework.  I'm
attaching 2 R files and pasting in the readme.

I would especially like to know if I'm doing anything that breaks
.Random.seed or other things that R's parallel uses in the
environment.

In case you don't want to wrestle with attachments, the same files are
online in our SVN

http://winstat.quant.ku.edu/svn/hpcexample/trunk/Ex66-ParallelSeedPrototype/

Hi.

In the description of your project in the file

  http://winstat.quant.ku.edu/svn/hpcexample/trunk/Ex66-ParallelSeedPrototype/README

you argue as follows

  Question: Why is this better than the simple old approach of
  setting the seeds within each run with a formula like
   
  set.seed(2345 + 10 * run)
   
  Answer: That does allow replication, but it does not assure
  that each run uses non-overlapping random number streams. It
  offers absolutely no assurance whatsoever that the runs are
  actually non-redundant.

The following demonstrates that the function set.seed() for
the default generator indeed allows to have correlated streams.

  step <- function(x)
  {
      x[x < 0] <- x[x < 0] + 2^32
      x <- (69069 * x + 1) %% 2^32
      x[x > 2^31] <- x[x > 2^31] - 2^32
      x
  }

  n <- 1000
  seed1 <- 124370417 # any seed
  seed2 <- step(seed1)

  set.seed(seed1)
  x <- runif(n)
  set.seed(seed2)
  y <- runif(n)

  rbind(seed1, seed2)
  table(x[-1] == y[-n])

The output is

             [,1]
  seed1 124370417
  seed2 205739774
  
  FALSE  TRUE 
      5   994 

This means that if the streams x, y are generated from the two
seeds above, then y is almost exactly equal to x shifted by 1.

What is the current state of your project?

Petr Savicky.