The use of the system resource /dev/random is more for cryptography, than for scientific simulations. Some application like SSH is blocking (in Stuart's situation) when the entropy pool is empty. Peter
On Mon, Feb 28, 2011 at 4:41 AM, Heiko Bauke <[email protected]> wrote: > Hi, > > On Sun, 27 Feb 2011 11:48:28 -0500 (EST) > "Robert G. Brown" <[email protected]> wrote: > > > The solution for nearly anyone needing large numbers of fast, high > > quality random numbers is going to be: Use a fast, high quality > > random number generator from e.g. the Gnu Scientific Library, and > > >>seed<< it from /dev/random, ensuring uniqueness of the seed(s) > > >>across the cluster > > I agree that for Monte Carlo simulations a fast, high quality (pseudo) > random number generator (PRNG) is more appropriate than /dev/{u}random. > However, seeding a PRNG randomly is imho a missconception. Even though > Monte Carlo algorithms utilize a pseudo random resource the final > result of a Monte Carlo simulation should be deterministic and > reproducible. Therefore, for scientific Monte Carlo applications one > should use a known seed. Parallel Monte Carlo applications may derive > streams of pseudo random numbers from a common base sequence by > splitting and leap frogging, see also > http://arxiv.org/abs/cond-mat/0609584 > > > Regards, > > Heiko > > > -- > -- Number Crunch Blog @ http://numbercrunch.de > -- Cluster Computing @ http://www.clustercomputing.de > -- Random numbers @ http://trng.berlios.de > -- Heiko Bauke @ http://www.mpi-hd.mpg.de/personalhomes/bauke > > > _______________________________________________ > Beowulf mailing list, [email protected] sponsored by Penguin Computing > To change your subscription (digest mode or unsubscribe) visit > http://www.beowulf.org/mailman/listinfo/beowulf >
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