Dear John, On Tue, 3 Jan 2012 16:26:25 -0500 John Salmon <john@thesalmons.org> wrote:
I am co-author of "Parallel Random Numbers, as Easy as 1, 2, 3". which recently won the best paper award at the IEEE/ACM SC'11 conference. I'm also co-author of the related Random123 library:
http://deshawresearch.com/resources_random123.html
My colleagues and I would like to contribute a similar library to Boost as well. This isn't just a "port" of the Random123 library. Boost's focus on C++ allows for both simplification and clarification of the ideas in the paper and the original library. I've done a preliminary draft of some code that fits nicely into the existing Boost Random library. It's incomplete, but I think there's enough for folks to look at and gauge further interest.
I would like to draw your attention to TRNG a C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations. It implements an interface which is basically an extension of the random number generator facility of the new C++ standard. See http://numbercrunch.de/trng/ for documentation and source code. I have not jet read your full paper "Parallel Random Numbers, as Easy as 1, 2, 3", however, I think your counter based generators should fit nicely into the framework of TRNG and allow for fair parallel Monte Carlo. (See http://pre.aps.org/abstract/PRE/v75/i6/e066701 or http://arxiv.org/abs/cond-mat/0609584 for the notion of »playing fair« in parallel Monte Carlo.) Heiko -- -- Cluster Computing @ http://www.clustercomputing.de -- Number Crunch Blog @ http://numbercrunch.de -- Heiko Bauke @ http://www.mpi-hd.mpg.de/personalhomes/bauke