Re: amber-developers: Verlet update time and ntt=3 parallel scaling

From: Robert Duke <>
Date: Wed, 7 May 2008 15:46:48 -0400

MT is known for the long period; Marsaglia's, which we use, is supposed to
be pretty good, based on reviews I read a couple of years ago, but who knows
if anyone ever tries to parallelize it (I sort of doubt it, looking at it).
All the common computer library, especially unix, rand() functions are junk;
one reason we don't use them. Currently, the parallel implementation with
the most press is something called SPRNG - probably a dozen papers out at
least, with emphasis on MC applications. I don't know what's under the
covers yet but will. There are other options also. And folks have studied
ways to take all the classic mechs (linear congruential, etc.) and
parallelize them, with mixed results. Now is not the time to race to a
conclusion on any of this stuff; we already have a mess on our hands with
how we have been treating stochastic processes, as far as I am concerned
(yes, I am conservative and a worrier).
Regards - Bob

----- Original Message -----
From: "Andreas Svrcek-Seiler" <>
To: <>
Sent: Wednesday, May 07, 2008 3:35 PM
Subject: Re: amber-developers: Verlet update time and ntt=3 parallel scaling

> Just 0.02$ more:
> In an ideal rng there are no correlations, but such a thing does not
> exist. The statistical properties
> of any subsequences should be indiscernible from physical white noise.
> Currently the best rng (as far as I know) is the Mersenne twister (MT)
> (see
> It offers periods up to 2**216091-1 (if one needs it) and
> as far as I remember any chosen seed gets you to somewhere (randomly,
> equally distributed) onto a number stream of length (period).
> Besides even the not architecture-optimized version of the MT
> is twice or more faster than (in)famous rand(), which I tested a while
> ago.
> I someone is really interested, he/she could try to contact MT's
> "father", Makoto Matsumoto, for answers to specifiec technical questions.
> He seem quite enthusiastic about people actually making use of his work.
> Unfortunately I didn't understand a word from the paper about MT.
> best,
> Andreas
> P.S.:It seems hard to imagine (for me) that there's a significant
> difference between a "good" and a "bad" rng when it comes to MD (e.g.
> driving a langevin-heatbath). Are you all sure you could tell the
> difference between a "real" rng and -say- the first 1000000 digits of pi
> repeated over and over driving a MD run when looking at the results?
> (nonetheless - in dubio mersenne twisto :-)
> )))))
> (((((
> ( O O )
> -------oOOO--(_)--OOOo-----------------------------------------------------
> o Wolfgang Andreas Svrcek-Seiler
> o (godzilla)
> .oooO Tel.:01-4277-52747
> ( ) Oooo.
> -------\
> ---( )--------------------------------------------------------
> \_) ) /
> (_/
> On Wed, 7 May 2008, Robert Duke wrote:
>> Well, at least in my reading so far on the subject, this is not the case.
>> There ARE correlations in any pseudo random number generator, and you are
>> not guaranteed of getting a proper distribution unless you have deeper
>> knowledge of the rng algorithm itself, and essentially start with one
>> seed and from there select "leapfrog" points in the deterministic
>> sequence of the rng. That is at least what I have read so far, but I have
>> not read widely; this stuff is in the physics literature, and I am
>> preoccupied at the moment trying to move other mountains, so I am not all
>> over it just yet. So given recent surprises with rng issues, I feel
>> fairly vindicated in not jumping on the "simple" solution here and just
>> generating a bunch of random seeds in parallel. As I read more, I will
>> know more, but I think what you propose here is potentially a really
>> really bad idea, and I would recommend against just trying it because a
>> lot of bad work can be done before the sensitive test case turns up that
>> starts making you wonder. The rng we use is supposed to be pretty good,
>> but I need to read more about it (Marsaglia's), and put it in a proper
>> context relative to current work on parallel rng's. I am at the point
>> where I will sort of promise to come up with something, given that I am
>> still employed, but I won't put anything out unless I am absolutely
>> certain that it generates a good sequence of random numbers (and I won't
>> go any further than saying I will get rng enhancements into pmemd for 11;
>> hopefully I will actually have some usable patches before that, but right
>> now I am preoccupied).
>> Regards - Bob
>> ----- Original Message ----- From: "Ross Walker" <>
>> To: <>
>> Sent: Wednesday, May 07, 2008 1:53 PM
>> Subject: RE: amber-developers: Verlet update time and ntt=3 parallel
>> scaling
>>> As far as I can tell if our random number generator is any good - which
>>> I
>>> don't know if we have properly checked or not - two sets of random
>>> numbers
>>> from different seeds should not have any correlation. Thus it should be
>>> equally correct (statistically) to do a Langevin run with each processor
>>> having its own random number stream - with simply different seeds for
>>> each
>>> mpi thread. This should be equivalent to having a single random number
>>> stream shared between all processors where each processor makes sure it
>>> doesn't use the same portion of the stream as other processors.
>>> Of course the first option makes testing in parallel difficult but then
>>> we
>>> only get about 300 steps or so matching anyway.
>>> So perhaps we should have two modes of operation (controlled in $cntrl
>>> maybe).
>>> A testing mode in which it does exactly what we have now and a
>>> production
>>> mode in which each thread uses its own random number stream. The
>>> question is
>>> how to set ig on each processor. One option would be for the master to
>>> use
>>> IG from &cntrl and then each mpi task add a successively bigger prime
>>> number
>>> to IG and use that (ig+3,+5,+7,+11 etc...). Another option would be for
>>> each
>>> processor to just add its task ID to ig but this may not be safe since
>>> it is
>>> possible that two random number streams for IG and IG+1 have some
>>> correlation - although I think this is purely hearsay and again I don't
>>> think it has been checked.
>>> These approaches would at least be reproducible on a given number of
>>> processors - for sander at least, perhaps not for PMEMD.
>>> Comments?
>>> /\
>>> \/
>>> |\oss Walker
>>> | Assistant Research Professor |
>>> | San Diego Supercomputer Center |
>>> | Tel: +1 858 822 0854 | EMail:- |
>>> | | PGP Key available on request |
>>> Note: Electronic Mail is not secure, has no guarantee of delivery, may
>>> not
>>> be read every day, and should not be used for urgent or sensitive
>>> issues.
Received on Sun May 11 2008 - 06:07:15 PDT
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