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- From: dak@tabaqui.informatik.rwth-aachen.de (David Kastrup)
- Newsgroups: sci.math.num-analysis
- Subject: Re: Distributed Random Number Generation
- Message-ID: <dak.716387354@tabaqui>
- Date: 13 Sep 92 12:29:14 GMT
- References: <h_8yzkk@rpi.edu> <DAVEG.92Sep13010611@synaptx.synaptics.com>
- Sender: news@Urmel.Informatik.RWTH-Aachen.DE (Newsfiles Owner)
- Organization: Rechnerbetrieb Informatik / RWTH Aachen
- Lines: 23
- Nntp-Posting-Host: tabaqui
-
- daveg@synaptics.com (Dave Gillespie) writes:
-
- >In article <h_8yzkk@rpi.edu> maniattb@cs.rpi.edu (Bill Maniatty) writes:
- >> I have a large distributed stochastic model (runs on MasPar MP-1 with 2,048
- >> processing elements). I'm not an expert on random number generation, but
- >> I need to simultaneously g enerate different ``Random'' sequences on each
- >> node.
-
- >If the nodes must be independent, then it would probably work pretty
- >well to use one random number generator, say, linear congruential,
- >to create a sequence of 2048 seeds for a different type of generator,
- >say additive congruential, running in parallel on the various nodes.
-
- This idea is really bad, because it ensures that no two generators will
- give the same number at one moment (or even always the same). Besides, random
- number generators are usually not designed to produce uncorrelated
- numbers at ARBITRARY distances in their sequence, so you would probably
- fail even simple tests terribly. As I said before, the only mathematically
- safe way is to use ONE (and only one) generator of very high quality to
- produce values in turn. This is because the mathematics for a good RNG
- can only be ensured with regard to itself, not to other instances of it
- (different seeds), and certainly not to different RNGs without further
- information.
-