[Mitgcm-support] [Fwd: Re: TAF bug for tangent linear]

[mitgcm-support at dev.mitgcm.org]

-------- Original Message --------
Subject: Re: TAF bug for tangent linear
Date: Thu, 12 Sep 2002 11:29:52 +0200
From: Ralf Giering <Ralf.Giering at fastopt.de>
Organization: FastOpt
To: heimbach at MIT.EDU
References: <3D7F660E.6010904 at mit.edu>

Hi Patrick,

That was indeed a general problem.
I have fixed it by saving the input variables on auxiliary variables
and reset the input variables before calling the linear routine the second
time.

I have not choosen the alternative, which is to recalculate the overwritten
input variables because, in its extreme, that might require to recompute a
lot from scratch. In your example the recomputation is trivial.

In addtion TAF gives an information message to the user in this case.
I have installed the new version TAF 1.4.12 on through and twain.

Ralf


On Wednesday 11 September 2002 05:49 pm, you wrote:
 > Hi Ralf,
 >
 > there is a problem with the forward mode of TAF
 > when exploiting self-adjointness.
 >
 > What happens is that in S/R g_solve_for_pressure
 > cg2d is called first to compute the g_... quantities
 > (g_cg2d_b,g_cg2d_x),
 > then called again to calculate the actual state
 > (cg2d_b,cg2d_x).
 > Before the second call the indices should be reset, thus
 >        firstresidual = 0.
 >        lastresidual = 0.
 >        numiters = cg2dmaxiters
 > but the reset is missing.
 >
 > The flow directive should have the information,
 > since the correct resetting is done in the adjoint code:
 >
 > C----------------------------------------
 > C subroutine  cg2d
 > C----------------------------------------
 > CADJ SUBROUTINE cg2d ADNAME  = cg2d
 > CADJ SUBROUTINE cg2d FTLNAME = cg2d
 > CADJ SUBROUTINE cg2d INPUT   = 1,2,3,4,5,6
 > CADJ SUBROUTINE cg2d OUTPUT  =   2,3,4,5
 > CADJ SUBROUTINE cg2d ACTIVE  = 1,2
 > CADJ SUBROUTINE cg2d DEPEND  =           6
 >
 >
 > Another issue (or, why I do all this) is that
 > I try to do forward mode vs. finite difference gradient checks.
 > Assuming that
 >     g_fc = (grad J)_(ith-component) * (delta xx)_(ith-component)
 > I should be able to recover (grad J)_(ith-component)
 > by setting
 >     (delta xx)_(ith-component) = 1.
 > (all others = 0.).
 > Well, I get the correct order of magnitude,
 > but not really correct gradients.
 > Do you have an idea what else could go wrong
 > (I've tried it with my above hand-fix).
 >
 > Cheers
 > Patrick

-- 
###################################################
  Dr. Ralf Giering
  FastOpt
  Martinistr. 21
  20251, Hamburg, Germany
  Tel. : +49 40 48096347
  Fax  : +49 40 48096357
  Email: Ralf.Giering at FastOpt.de
  URL  : http://www.FastOpt.de
###################################################

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Patrick Heimbach     Massachusetts Institute of Technology
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