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Date:      Sun, 05 Jan 2003 12:05:33 -0800
From:      Terry Lambert <tlambert2@mindspring.com>
To:        Rahul Siddharthan <rsidd@online.fr>
Cc:        Brett Glass <brett@lariat.org>, Greg 'groggy' Lehey <grog@FreeBSD.org>, chat@FreeBSD.org
Subject:   Re: Bystander shot by a spam filter
Message-ID:  <3E18900D.10F82814@mindspring.com>
References:  <3E18073C.68182FE4@mindspring.com> <4.3.2.7.2.20030104201251.029387d0@localhost> <4.3.2.7.2.20030104112015.026a5530@localhost> <4.3.2.7.2.20030104201251.029387d0@localhost> <4.3.2.7.2.20030104202908.03c3b100@localhost> <20030105073804.GA72674@wantadilla.lemis.com> <20030105074923.GA4956@papagena.rockefeller.edu> <3E18073C.68182FE4@mindspring.com> <4.3.2.7.2.20030105120224.029377d0@localhost> <20030105192556.GA526@papagena.rockefeller.edu>

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Rahul Siddharthan wrote:
> It is interesting, in fact, that gcc does well in all such problems.
> It doesn't do very well in Gauss-Siedel relaxation (which is a fairly
> straightforward iterative method) and does quite badly in a
> monte-carlo integration (which is basically just one long loop with
> calls to a random number generator and the function evaluator).

Monte Carlo is where I've personally noticed a difference, FWIW.

There are a number of packages commonly used in physics work,
out of both Berkeley and LBL, which perform Monte Carlo generation
of relativistically invariant P-N and N-N collisions, for the
purposes of pair production.  You then use your theoretical physics
to constrain the resulting allowable values, which then simulates
what you can expect, according to your theory, were you to run a
physical experiment in a large accelerator/collider.  It's a useful
way of testing theories vs. observed data, to see where they fall
down (or not -- one hopes...).

In any case, the Intel compiler gives significantly better numbers.


-- Terry

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