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revision 1.7 by cnh, Thu Oct 25 18:36:55 2001 UTC revision 1.20 by edhill, Wed Apr 5 02:27:33 2006 UTC
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1  % $Header$  % $Header$
2  % $Name$  % $Name$
3    
4    Author: Patrick Heimbach
5    
6  {\sf Automatic differentiation} (AD), also referred to as algorithmic  {\sf Automatic differentiation} (AD), also referred to as algorithmic
7  (or, more loosely, computational) differentiation, involves  (or, more loosely, computational) differentiation, involves
8  automatically deriving code to calculate  automatically deriving code to calculate partial derivatives from an
9  partial derivatives from an existing fully non-linear prognostic code.  existing fully non-linear prognostic code.  (see \cite{gri:00}).  A
10  (see \cite{gri:00}).  software tool is used that parses and transforms source files
11  A software tool is used that parses and transforms source files  according to a set of linguistic and mathematical rules.  AD tools are
12  according to a set of linguistic and mathematical rules.  like source-to-source translators in that they parse a program code as
13  AD tools are like source-to-source translators in that  input and produce a new program code as output.  However, unlike a
14  they parse a program code as input and produce a new program code  pure source-to-source translation, the output program represents a new
15  as output.  algorithm, such as the evaluation of the Jacobian, the Hessian, or
16  However, unlike a pure source-to-source translation, the output program  higher derivative operators.  In principle, a variety of derived
17  represents a new algorithm, such as the evaluation of the  algorithms can be generated automatically in this way.
18  Jacobian, the Hessian, or higher derivative operators.  
19  In principle, a variety of derived algorithms  MITgcm has been adapted for use with the Tangent linear and Adjoint
20  can be generated automatically in this way.  Model Compiler (TAMC) and its successor TAF (Transformation of
21    Algorithms in Fortran), developed by Ralf Giering (\cite{gie-kam:98},
22  The MITGCM has been adapted for use with the  \cite{gie:99,gie:00}).  The first application of the adjoint of MITgcm
23  Tangent linear and Adjoint Model Compiler (TAMC) and its successor TAF  for sensitivity studies has been published by \cite{maro-eta:99}.
24  (Transformation of Algorithms in Fortran), developed  \cite{sta-eta:97,sta-eta:01} use MITgcm and its adjoint for ocean
25  by Ralf Giering (\cite{gie-kam:98}, \cite{gie:99,gie:00}).  state estimation studies.  In the following we shall refer to TAMC and
26  The first application of the adjoint of the MITGCM for sensitivity  TAF synonymously, except were explicitly stated otherwise.
27  studies has been published by \cite{maro-eta:99}.  
28  \cite{sta-eta:97,sta-eta:01} use the MITGCM and its adjoint  TAMC exploits the chain rule for computing the first derivative of a
29  for ocean state estimation studies.  function with respect to a set of input variables.  Treating a given
30  In the following we shall refer to TAMC and TAF synonymously,  forward code as a composition of operations -- each line representing
31  except were explicitly stated otherwise.  a compositional element, the chain rule is rigorously applied to the
32    code, line by line. The resulting tangent linear or adjoint code,
33  TAMC exploits the chain rule for computing the first  then, may be thought of as the composition in forward or reverse
34  derivative of a function with  order, respectively, of the Jacobian matrices of the forward code's
35  respect to a set of input variables.  compositional elements.
 Treating a given forward code as a composition of operations --  
 each line representing a compositional element, the chain rule is  
 rigorously applied to the code, line by line. The resulting  
 tangent linear or adjoint code,  
 then, may be thought of as the composition in  
 forward or reverse order, respectively, of the  
 Jacobian matrices of the forward code's compositional elements.  
36    
37  %**********************************************************************  %**********************************************************************
38  \section{Some basic algebra}  \section{Some basic algebra}
39  \label{sec_ad_algebra}  \label{sec_ad_algebra}
40    \begin{rawhtml}
41    <!-- CMIREDIR:sec_ad_algebra: -->
42    \end{rawhtml}
43  %**********************************************************************  %**********************************************************************
44    
45  Let $ \cal{M} $ be a general nonlinear, model, i.e. a  Let $ \cal{M} $ be a general nonlinear, model, i.e. a
# Line 557  Because of the local character of the de Line 555  Because of the local character of the de
555  (a derivative is defined w.r.t. a point along the trajectory),  (a derivative is defined w.r.t. a point along the trajectory),
556  the intermediate results of the model trajectory  the intermediate results of the model trajectory
557  $\vec{v}^{(\lambda+1)}={\cal M}_{\lambda}(v^{(\lambda)})$  $\vec{v}^{(\lambda+1)}={\cal M}_{\lambda}(v^{(\lambda)})$
558  are needed to evaluate the intermediate Jacobian  may be required to evaluate the intermediate Jacobian
559  $M_{\lambda}|_{\vec{v}^{(\lambda)}} \, \delta \vec{v}^{(\lambda)} $.  $M_{\lambda}|_{\vec{v}^{(\lambda)}} \, \delta \vec{v}^{(\lambda)} $.
560    This is the case e.g. for nonlinear expressions
561    (momentum advection, nonlinear equation of state), state-dependent
562    conditional statements (parameterization schemes).
563  In the forward mode, the intermediate results are required  In the forward mode, the intermediate results are required
564  in the same order as computed by the full forward model ${\cal M}$,  in the same order as computed by the full forward model ${\cal M}$,
565  but in the reverse mode they are required in the reverse order.  but in the reverse mode they are required in the reverse order.
# Line 569  point of evaluation has to be recomputed Line 570  point of evaluation has to be recomputed
570    
571  A method to balance the amount of recomputations vs.  A method to balance the amount of recomputations vs.
572  storage requirements is called {\sf checkpointing}  storage requirements is called {\sf checkpointing}
573  (e.g. \cite{res-eta:98}).  (e.g. \cite{gri:92}, \cite{res-eta:98}).
574  It is depicted in \ref{fig:3levelcheck} for a 3-level checkpointing  It is depicted in \ref{fig:3levelcheck} for a 3-level checkpointing
575  [as an example, we give explicit numbers for a 3-day  [as an example, we give explicit numbers for a 3-day
576  integration with a 1-hourly timestep in square brackets].  integration with a 1-hourly timestep in square brackets].
# Line 580  In a first step, the model trajectory is Line 581  In a first step, the model trajectory is
581  $ {n}^{lev3} $ subsections [$ {n}^{lev3} $=3 1-day intervals],  $ {n}^{lev3} $ subsections [$ {n}^{lev3} $=3 1-day intervals],
582  with the label $lev3$ for this outermost loop.  with the label $lev3$ for this outermost loop.
583  The model is then integrated along the full trajectory,  The model is then integrated along the full trajectory,
584  and the model state stored only at every $ k_{i}^{lev3} $-th timestep  and the model state stored to disk only at every $ k_{i}^{lev3} $-th timestep
585  [i.e. 3 times, at  [i.e. 3 times, at
586  $ i = 0,1,2 $ corresponding to $ k_{i}^{lev3} = 0, 24, 48 $].  $ i = 0,1,2 $ corresponding to $ k_{i}^{lev3} = 0, 24, 48 $].
587    In addition, the cost function is computed, if needed.
588  %  %
589  \item [$lev2$]  \item [$lev2$]
590  In a second step each subsection itself is divided into  In a second step each subsection itself is divided into
591  $ {n}^{lev2} $ sub-subsections  $ {n}^{lev2} $ subsections
592  [$ {n}^{lev2} $=4 6-hour intervals per subsection].  [$ {n}^{lev2} $=4 6-hour intervals per subsection].
593  The model picks up at the last outermost dumped state  The model picks up at the last outermost dumped state
594  $ v_{k_{n}^{lev3}} $ and is integrated forward in time along  $ v_{k_{n}^{lev3}} $ and is integrated forward in time along
595  the last subsection, with the label $lev2$ for this    the last subsection, with the label $lev2$ for this  
596  intermediate loop.  intermediate loop.
597  The model state is now stored at every $ k_{i}^{lev2} $-th  The model state is now stored to disk at every $ k_{i}^{lev2} $-th
598  timestep  timestep
599  [i.e. 4 times, at  [i.e. 4 times, at
600  $ i = 0,1,2,3 $ corresponding to $ k_{i}^{lev2} = 48, 54, 60, 66 $].  $ i = 0,1,2,3 $ corresponding to $ k_{i}^{lev2} = 48, 54, 60, 66 $].
# Line 600  $ i = 0,1,2,3 $ corresponding to $ k_{i} Line 602  $ i = 0,1,2,3 $ corresponding to $ k_{i}
602  \item [$lev1$]  \item [$lev1$]
603  Finally, the model picks up at the last intermediate dump state  Finally, the model picks up at the last intermediate dump state
604  $ v_{k_{n}^{lev2}} $ and is integrated forward in time along  $ v_{k_{n}^{lev2}} $ and is integrated forward in time along
605  the last sub-subsection, with the label $lev1$ for this    the last subsection, with the label $lev1$ for this  
606  intermediate loop.  intermediate loop.
607  Within this sub-subsection only, the model state is stored  Within this sub-subsection only, parts of the model state is stored
608  at every timestep  to memory at every timestep
609  [i.e. every hour $ i=0,...,5$ corresponding to  [i.e. every hour $ i=0,...,5$ corresponding to
610  $ k_{i}^{lev1} = 66, 67, \ldots, 71 $].  $ k_{i}^{lev1} = 66, 67, \ldots, 71 $].
611  Thus, the  final state $ v_n = v_{k_{n}^{lev1}} $ is reached  The  final state $ v_n = v_{k_{n}^{lev1}} $ is reached
612  and the model state of all  proceeding timesteps along the last  and the model state of all preceding timesteps along the last
613  sub-subsections are available, enabling integration backwards  innermost subsection are available, enabling integration backwards
614  in time along the last sub-subsection.  in time along the last subsection.
615  Thus, the adjoint can be computed along this last  The adjoint can thus be computed along this last
616  sub-subsection $k_{n}^{lev2}$.  subsection $k_{n}^{lev2}$.
617  %  %
618  \end{itemize}  \end{itemize}
619  %  %
620  This procedure is repeated consecutively for each previous  This procedure is repeated consecutively for each previous
621  sub-subsection $k_{n-1}^{lev2}, \ldots, k_{1}^{lev2} $  subsection $k_{n-1}^{lev2}, \ldots, k_{1}^{lev2} $
622  carrying the adjoint computation to the initial time  carrying the adjoint computation to the initial time
623  of the subsection $k_{n}^{lev3}$.  of the subsection $k_{n}^{lev3}$.
624  Then, the procedure is repeated for the previous subsection  Then, the procedure is repeated for the previous subsection
# Line 627  $k_{1}^{lev3}$. Line 629  $k_{1}^{lev3}$.
629  For the full model trajectory of  For the full model trajectory of
630  $ n^{lev3} \cdot n^{lev2} \cdot n^{lev1} $ timesteps  $ n^{lev3} \cdot n^{lev2} \cdot n^{lev1} $ timesteps
631  the required storing of the model state was significantly reduced to  the required storing of the model state was significantly reduced to
632  $ n^{lev1} + n^{lev2} + n^{lev3} $  $ n^{lev2} + n^{lev3} $ to disk and roughly $ n^{lev1} $ to memory
633  [i.e. for the 3-day integration with a total oof 72 timesteps  [i.e. for the 3-day integration with a total oof 72 timesteps
634  the model state was stored 13 times].  the model state was stored 7 times to disk and roughly 6 times
635    to memory].
636  This saving in memory comes at a cost of a required  This saving in memory comes at a cost of a required
637  3 full forward integrations of the model (one for each  3 full forward integrations of the model (one for each
638  checkpointing level).  checkpointing level).
639  The balance of storage vs. recomputation certainly depends  The optimal balance of storage vs. recomputation certainly depends
640  on the computing resources available.  on the computing resources available and may be adjusted by
641    adjusting the partitioning among the
642    $ n^{lev3}, \,\, n^{lev2}, \,\, n^{lev1} $.
643    
644  \begin{figure}[t!]  \begin{figure}[t!]
645  \begin{center}  \begin{center}
# Line 664  Schematic view of intermediate dump and Line 669  Schematic view of intermediate dump and
669  % \subsection{Error covariance estimate and Hessian matrix}  % \subsection{Error covariance estimate and Hessian matrix}
670  % \label{sec_hessian}  % \label{sec_hessian}
671    
672  \newpage  \newpage
673    
674  %**********************************************************************  %**********************************************************************
675  \section{AD-specific setup by example: sensitivity of carbon sequestration}  \section{TLM and ADM generation in general}
676  \label{sec_ad_setup_ex}  \label{sec_ad_setup_gen}
677    \begin{rawhtml}
678    <!-- CMIREDIR:sec_ad_setup_gen: -->
679    \end{rawhtml}
680  %**********************************************************************  %**********************************************************************
681    
682  The MITGCM has been adapted to enable AD using TAMC or TAF.  In this section we describe in a general fashion
683  The present description, therefore, is specific to the  the parts of the code that are relevant for automatic
684  use of TAMC or TAF as AD tool.  differentiation using the software tool TAF.
685  The following sections describe the steps which are necessary to  
686  generate a tangent linear or adjoint model of the MITGCM.  \input{part5/doc_ad_the_model}
687  We take as an example the sensitivity of carbon sequestration  
688  in the ocean.  The basic flow is depicted in \ref{fig:adthemodel}.
689  The AD-relevant hooks in the code are sketched in  If CPP option \texttt{ALLOW\_AUTODIFF\_TAMC} is defined,
690  \ref{fig:adthemodel}, \ref{fig:adthemain}.  the driver routine
691    {\it the\_model\_main}, instead of calling {\it the\_main\_loop},
692  \subsection{Overview of the experiment}  invokes the adjoint of this routine, {\it adthe\_main\_loop}
693    (case \texttt{\#define ALLOW\_ADJOINT\_RUN}), or
694  We describe an adjoint sensitivity analysis of out-gassing from  the tangent linear of this routine {\it g\_the\_main\_loop}
695  the ocean into the atmosphere of a carbon-like tracer injected  (case \texttt{\#define ALLOW\_TANGENTLINEAR\_RUN}),
696  into the ocean interior (see \cite{hil-eta:01}).  which are the toplevel routines in terms of automatic differentiation.
697    The routines {\it adthe\_main\_loop} or {\it g\_the\_main\_loop}
698  \subsubsection{Passive tracer equation}  are generated by TAF.
699    It contains both the forward integration of the full model, the
700  For this work the MITGCM was augmented with a thermodynamically  cost function calculation,
701  inactive tracer, $C$. Tracer residing in the ocean  any additional storing that is required for efficient checkpointing,
702  model surface layer is out-gassed according to a relaxation time scale,  and the reverse integration of the adjoint model.
703  $\mu$. Within the ocean interior, the tracer is passively advected  
704  by the ocean model currents. The full equation for the time evolution  [DESCRIBE IN A SEPARATE SECTION THE WORKING OF THE TLM]
705  %  
706  \begin{equation}  In Fig. \ref{fig:adthemodel}
707  \label{carbon_ddt}  the structure of {\it adthe\_main\_loop} has been strongly
708  \frac{\partial C}{\partial t} \, = \,  simplified to focus on the essentials; in particular, no checkpointing
709  -U\cdot \nabla C \, - \, \mu C \, + \, \Gamma(C) \,+ \, S  procedures are shown here.
710  \end{equation}  Prior to the call of {\it adthe\_main\_loop}, the routine
711  %  {\it ctrl\_unpack} is invoked to unpack the control vector
712  also includes a source term $S$. This term  or initialise the control variables.
713  represents interior sources of $C$ such as would arise due to  Following the call of {\it adthe\_main\_loop},
714  direct injection.  the routine {\it ctrl\_pack}
715  The velocity term, $U$, is the sum of the  is invoked to pack the control vector
716  model Eulerian circulation and an eddy-induced velocity, the latter  (cf. Section \ref{section_ctrl}).
717  parameterized according to Gent/McWilliams  If gradient checks are to be performed, the option
718  (\cite{gen-mcw:90, gen-eta:95}).  {\tt ALLOW\_GRADIENT\_CHECK} is defined. In this case
719  The convection function, $\Gamma$, mixes $C$ vertically wherever the  the driver routine {\it grdchk\_main} is called after
720  fluid is locally statically unstable.  the gradient has been computed via the adjoint
721    (cf. Section \ref{section_grdchk}).
 The out-gassing time scale, $\mu$, in eqn. (\ref{carbon_ddt})  
 is set so that \( 1/\mu \sim 1 \ \mathrm{year} \) for the surface  
 ocean and $\mu=0$ elsewhere. With this value, eqn. (\ref{carbon_ddt})  
 is valid as a prognostic equation for small perturbations in oceanic  
 carbon concentrations. This configuration provides a  
 powerful tool for examining the impact of large-scale ocean circulation  
 on $ CO_2 $ out-gassing due to interior injections.  
 As source we choose a constant in time injection of  
 $ S = 1 \,\, {\rm mol / s}$.  
   
 \subsubsection{Model configuration}  
   
 The model configuration employed has a constant  
 $4^\circ \times 4^\circ$ resolution horizontal grid and realistic  
 geography and bathymetry. Twenty vertical layers are used with  
 vertical spacing ranging  
 from 50 m near the surface to 815 m at depth.  
 Driven to steady-state by climatological wind-stress, heat and  
 fresh-water forcing the model reproduces well known large-scale  
 features of the ocean general circulation.  
   
 \subsubsection{Out-gassing cost function}  
   
 To quantify and understand out-gassing due to injections of $C$  
 in eqn. (\ref{carbon_ddt}),  
 we define a cost function $ {\cal J} $ that measures the total amount of  
 tracer out-gassed at each timestep:  
 %  
 \begin{equation}  
 \label{cost_tracer}  
 {\cal J}(t=T)=\int_{t=0}^{t=T}\int_{A} \mu C \, dA \, dt  
 \end{equation}  
 %  
 Equation(\ref{cost_tracer}) integrates the out-gassing term, $\mu C$,  
 from (\ref{carbon_ddt})  
 over the entire ocean surface area, $A$, and accumulates it  
 up to time $T$.  
 Physically, ${\cal J}$ can be thought of as representing the amount of  
 $CO_2$ that our model predicts would be out-gassed following an  
 injection at rate $S$.  
 The sensitivity of ${\cal J}$ to the spatial location of $S$,  
 $\frac{\partial {\cal J}}{\partial S}$,  
 can be used to identify regions from which circulation  
 would cause $CO_2$ to rapidly out-gas following injection  
 and regions in which $CO_2$ injections would remain effectively  
 sequestered within the ocean.  
   
 \subsection{Code configuration}  
   
 The model configuration for this experiment resides under the  
 directory {\it verification/carbon/}.  
 The code customization routines are in {\it verification/carbon/code/}:  
 %  
 \begin{itemize}  
 %  
 \item {\it .genmakerc}  
 %  
 \item {\it COST\_CPPOPTIONS.h}  
 %  
 \item {\it CPP\_EEOPTIONS.h}  
 %  
 \item {\it CPP\_OPTIONS.h}  
 %  
 \item {\it CTRL\_OPTIONS.h}  
 %  
 \item {\it ECCO\_OPTIONS.h}  
 %  
 \item {\it SIZE.h}  
 %  
 \item {\it adcommon.h}  
 %  
 \item {\it tamc.h}  
 %  
 \end{itemize}  
 %  
 The runtime flag and parameters settings are contained in  
 {\it verification/carbon/input/},  
 together with the forcing fields and and restart files:  
 %  
 \begin{itemize}  
 %  
 \item {\it data}  
 %  
 \item {\it data.cost}  
 %  
 \item {\it data.ctrl}  
 %  
 \item {\it data.gmredi}  
 %  
 \item {\it data.grdchk}  
 %  
 \item {\it data.optim}  
 %  
 \item {\it data.pkg}  
 %  
 \item {\it eedata}  
 %  
 \item {\it topog.bin}  
 %  
 \item {\it windx.bin, windy.bin}  
 %  
 \item {\it salt.bin, theta.bin}  
 %  
 \item {\it SSS.bin, SST.bin}  
 %  
 \item {\it pickup*}  
 %  
 \end{itemize}  
 %  
 Finally, the file to generate the adjoint code resides in  
 $ adjoint/ $:  
 %  
 \begin{itemize}  
 %  
 \item {\it makefile}  
 %  
 \end{itemize}  
 %  
722    
723  Below we describe the customizations of this files which are  %------------------------------------------------------------------
 specific to this experiment.  
724    
725  \subsubsection{File {\it .genmakerc}}  \subsection{General setup
726  This file overwrites default settings of {\it genmake}.  \label{section_ad_setup}}
 In the present example it is used to switch on the following  
 packages which are related to automatic differentiation  
 and are disabled by default: \\  
 \hspace*{4ex} {\tt set ENABLE=( autodiff cost ctrl ecco gmredi grdchk kpp )}  \\  
 Other packages which are not needed are switched off: \\  
 \hspace*{4ex} {\tt set DISABLE=( aim obcs zonal\_filt shap\_filt cal exf )}  
   
 \subsubsection{File {\it COST\_CPPOPTIONS.h,  CTRL\_OPTIONS.h}}  
   
 These files used to contain package-specific CPP-options  
 (see Section \ref{???}).  
 For technical reasons those options have been grouped together  
 in the file {\it ECCO\_OPTIONS.h}.  
 To retain the modularity, the files have been kept and contain  
 the standard include of the {\it CPP\_OPTIONS.h} file.  
   
 \subsubsection{File {\it CPP\_EEOPTIONS.h}}  
   
 This file contains 'wrapper'-specific CPP options.  
 It only needs to be changed if the code is to be run  
 in a parallel environment (see Section \ref{???}).  
   
 \subsubsection{File {\it CPP\_OPTIONS.h}}  
   
 This file contains model-specific CPP options  
 (see Section \ref{???}).  
 Most options are related to the forward model setup.  
 They are identical to the global steady circulation setup of  
 {\it verification/exp2/}.  
 The three options specific to this experiment are \\  
 \hspace*{4ex} {\tt \#define ALLOW\_PASSIVE\_TRACER} \\  
 This flag enables the code to carry through the  
 advection/diffusion of a passive tracer along the  
 model integration. \\  
 \hspace*{4ex} {\tt \#define ALLOW\_MIT\_ADJOINT\_RUN} \\  
 This flag enables the inclusion of some AD-related fields  
 concerning initialization, link between control variables  
 and forward model variables, and the call to the top-level  
 forward/adjoint subroutine {\it adthe\_main\_loop}  
 instead of {\it the\_main\_loop}. \\  
 \hspace*{4ex} {\tt \#define ALLOW\_GRADIENT\_CHECK} \\  
 This flag enables the gradient check package.  
 After computing the unperturbed cost function and its gradient,  
 a series of computations are performed for which \\  
 $\bullet$ an element of the control vector is perturbed \\  
 $\bullet$ the cost function w.r.t. the perturbed element is  
 computed \\  
 $\bullet$ the difference between the perturbed and unperturbed  
 cost function is computed to compute the finite difference gradient \\  
 $\bullet$ the finite difference gradient is compared with the  
 adjoint-generated gradient.  
 The gradient check package is further described in Section ???.  
727    
728  \subsubsection{File {\it ECCO\_OPTIONS.h}}  In order to configure AD-related setups the following packages need
729    to be enabled:
730    {\it
731    \begin{table}[h!]
732    \begin{tabular}{l}
733    autodiff \\
734    ctrl \\
735    cost \\
736    grdchk \\
737    \end{tabular}
738    \end{table}
739    }
740    The packages are enabled by adding them to your experiment-specific
741    configuration file
742    {\it packages.conf} (see Section ???).
743    
744  The CPP options of several AD-related packages are grouped  The following AD-specific CPP option files need to be customized:
 in this file:  
745  %  %
746  \begin{itemize}  \begin{itemize}
747  %  %
748  \item  \item {\it ECCO\_CPPOPTIONS.h} \\
749  Adjoint support package: {\it pkg/autodiff/} \\  This header file collects CPP options for the packages
750  This package contains hand-written adjoint code such as  {\it autodiff, cost, ctrl} as well as AD-unrelated options for
751  active file handling, flow directives for files which must not  the external forcing package {\it exf}.
752  be differentiated, and TAMC-specific header files. \\  \footnote{NOTE: These options are not set in their package-specific
753  \hspace*{4ex} {\tt \#define ALLOW\_AUTODIFF\_TAMC} \\  headers such as {\it COST\_CPPOPTIONS.h}, but are instead collected
754  defines TAMC-related features in the code. \\  in the single header file {\it ECCO\_CPPOPTIONS.h}.
755  \hspace*{4ex} {\tt \#define ALLOW\_TAMC\_CHECKPOINTING} \\  The package-specific header files serve as simple
756  enables the checkpointing feature of TAMC  placeholders at this point.}
757  (see Section \ref{???}).  %
758  In the present example a 3-level checkpointing is implemented.  \item {\it tamc.h} \\
759  The code contains the relevant store directives, common block  This header configures the splitting of the time stepping loop
760  and tape initializations, storing key computation,  w.r.t. the 3-level checkpointing (see section ???).
761  and loop index handling.  
 The checkpointing length at each level is defined in  
 file {\it tamc.h}, cf. below.  
 %  
 \item Cost function package: {\it pkg/cost/} \\  
 This package contains all relevant routines for  
 initializing, accumulating and finalizing the cost function  
 (see Section \ref{???}). \\  
 \hspace*{4ex} {\tt \#define ALLOW\_COST} \\  
 enables all general aspects of the cost function handling,  
 in particular the hooks in the forward code for  
 initializing, accumulating and finalizing the cost function. \\  
 \hspace*{4ex} {\tt \#define ALLOW\_COST\_TRACER} \\  
 includes the call to the cost function for this  
 particular experiment, eqn. (\ref{cost_tracer}).  
 %  
 \item Control variable package: {\it pkg/ctrl/} \\  
 This package contains all relevant routines for  
 the handling of the control vector.  
 Each control variable can be enabled/disabled with its own flag: \\  
 \begin{tabular}{ll}  
 \hspace*{2ex} {\tt \#define ALLOW\_THETA0\_CONTROL} &  
 initial temperature \\  
 \hspace*{2ex} {\tt \#define ALLOW\_SALT0\_CONTROL} &  
 initial salinity \\  
 \hspace*{2ex} {\tt \#define ALLOW\_TR0\_CONTROL} &  
 initial passive tracer concentration \\  
 \hspace*{2ex} {\tt \#define ALLOW\_TAUU0\_CONTROL} &  
 zonal wind stress \\  
 \hspace*{2ex} {\tt \#define ALLOW\_TAUV0\_CONTROL} &  
 meridional wind stress \\  
 \hspace*{2ex} {\tt \#define ALLOW\_SFLUX0\_CONTROL} &  
 freshwater flux \\  
 \hspace*{2ex} {\tt \#define ALLOW\_HFLUX0\_CONTROL} &  
 heat flux \\  
 \hspace*{2ex} {\tt \#define ALLOW\_DIFFKR\_CONTROL} &  
 diapycnal diffusivity \\  
 \hspace*{2ex} {\tt \#undef ALLOW\_KAPPAGM\_CONTROL} &  
 isopycnal diffusivity \\  
 \end{tabular}  
762  %  %
763  \end{itemize}  \end{itemize}
764    
765  \subsubsection{File {\it SIZE.h}}  %------------------------------------------------------------------
   
 The file contains the grid point dimensions of the forward  
 model. It is identical to the {\it verification/exp2/}: \\  
 \hspace*{4ex} {\tt sNx = 90} \\  
 \hspace*{4ex} {\tt sNy = 40} \\  
 \hspace*{4ex} {\tt Nr = 20} \\  
 It corresponds to a single-tile/single-processor setup:  
 {\tt nSx = nSy = 1, nPx = nPy = 1},  
 with standard overlap dimensioning  
 {\tt OLx = OLy = 3}.  
   
 \subsubsection{File {\it adcommon.h}}  
   
 This file contains common blocks of some adjoint variables  
 that are generated by TAMC.  
 The common blocks are used by the adjoint support routine  
 {\it addummy\_in\_stepping} which needs to access those variables:  
   
 \begin{tabular}{ll}  
 \hspace*{4ex} {\tt common /addynvars\_r/} &  
 \hspace*{4ex} is related to {\it DYNVARS.h} \\  
 \hspace*{4ex} {\tt common /addynvars\_cd/} &  
 \hspace*{4ex} is related to {\it DYNVARS.h} \\  
 \hspace*{4ex} {\tt common /addynvars\_diffkr/} &  
 \hspace*{4ex} is related to {\it DYNVARS.h} \\  
 \hspace*{4ex} {\tt common /addynvars\_kapgm/} &  
 \hspace*{4ex} is related to {\it DYNVARS.h} \\  
 \hspace*{4ex} {\tt common /adtr1\_r/} &  
 \hspace*{4ex} is related to {\it TR1.h} \\  
 \hspace*{4ex} {\tt common /adffields/} &  
 \hspace*{4ex} is related to {\it FFIELDS.h}\\  
 \end{tabular}  
   
 Note that if the structure of the common block changes in the  
 above header files of the forward code, the structure  
 of the adjoint common blocks will change accordingly.  
 Thus, it has to be made sure that the structure of the  
 adjoint common block in the hand-written file {\it adcommon.h}  
 complies with the automatically generated adjoint common blocks  
 in {\it adjoint\_model.F}.  
766    
767  \subsubsection{File {\it tamc.h}}  \subsection{Building the AD code
768    \label{section_ad_build}}
769    
770  This routine contains the dimensions for TAMC checkpointing.  The build process of an AD code is very similar to building
771    the forward model. However, depending on which AD code one wishes
772    to generate, and on which AD tool is available (TAF or TAMC),
773    the following {\tt make} targets are available:
774    
775    \begin{table}[h!]
776    {\footnotesize
777    \begin{tabular}{ccll}
778    ~ & {\it AD-target} & {\it output} & {\it description} \\
779    \hline
780    \hline
781    (1) & {\tt <MODE><TOOL>only} & {\tt <MODE>\_<TOOL>\_output.f}  &
782    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
783    ~ & ~ & ~ & no {\tt make} dependencies on {\tt .F .h} \\
784    ~ & ~ & ~ & useful for compiling on remote platforms \\
785    \hline
786    (2) & {\tt <MODE><TOOL>} & {\tt <MODE>\_<TOOL>\_output.f}  &
787    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
788    ~ & ~ & ~ & includes {\tt make} dependencies on {\tt .F .h} \\
789    ~ & ~ & ~ & i.e. input for $<$TOOL$>$ may be re-generated \\
790    \hline
791    (3) & {\tt <MODE>all} & {\tt mitgcmuv\_<MODE>}  &
792    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
793    ~ & ~ & ~ & and compiles all code \\
794    ~ & ~ & ~ & (use of TAF is set as default) \\
795    \hline
796    \hline
797    \end{tabular}
798    }
799    \end{table}
800    %
801    Here, the following placeholders are used
802  %  %
803  \begin{itemize}  \begin{itemize}
804  %  %
805  \item {\tt \#ifdef ALLOW\_TAMC\_CHECKPOINTING} \\  \item [$<$TOOL$>$]
 3-level checkpointing is enabled, i.e. the timestepping  
 is divided into three different levels (see Section \ref{???}).  
 The model state of the outermost ({\tt nchklev\_3}) and the  
 intermediate ({\tt nchklev\_2}) timestepping loop are stored to file  
 (handled in {\it the\_main\_loop}).  
 The innermost loop ({\tt nchklev\_1})  
 avoids I/O by storing all required variables  
 to common blocks. This storing may also be necessary if  
 no checkpointing is chosen  
 (nonlinear functions, if-statements, iterative loops, ...).  
 In the present example the dimensions are chosen as follows: \\  
 \hspace*{4ex} {\tt nchklev\_1      =  36 } \\  
 \hspace*{4ex} {\tt nchklev\_2      =  30 } \\  
 \hspace*{4ex} {\tt nchklev\_3      =  60 } \\  
 To guarantee that the checkpointing intervals span the entire  
 integration period the following relation must be satisfied: \\  
 \hspace*{4ex} {\tt nchklev\_1*nchklev\_2*nchklev\_3 $ \ge $ nTimeSteps} \\  
 where {\tt nTimeSteps} is either specified in {\it data}  
 or computed via \\  
 \hspace*{4ex} {\tt nTimeSteps = (endTime-startTime)/deltaTClock }.  
 %  
 \item {\tt \#undef ALLOW\_TAMC\_CHECKPOINTING} \\  
 No checkpointing is enabled.  
 In this case the relevant counter is {\tt nchklev\_0}.  
 Similar to above, the following relation has to be satisfied \\  
 \hspace*{4ex} {\tt nchklev\_0 $ \ge $ nTimeSteps}.  
806  %  %
807  \end{itemize}  \begin{itemize}
   
 The following parameters may be worth describing: \\  
808  %  %
809  \hspace*{4ex} {\tt isbyte} \\  \item {\tt TAF}
810  \hspace*{4ex} {\tt maxpass} \\  \item {\tt TAMC}
 ~  
   
 \subsubsection{File {\it makefile}}  
   
 This file contains all relevant parameter flags and  
 lists to run TAMC or TAF.  
 It is assumed that TAMC is available to you, either locally,  
 being installed on your network, or remotely through the 'TAMC Utility'.  
 TAMC is called with the command {\tt tamc} followed by a  
 number of options. They are described in detail in the  
 TAMC manual \cite{gie:99}.  
 Here we briefly discuss the main flags used in the {\it makefile}  
811  %  %
 \begin{itemize}  
 \item [{\tt tamc}] {\tt  
 -input <variable names>  
 -output <variable name> -r4 ... \\  
 -toplevel <S/R name> -reverse <file names>  
 }  
812  \end{itemize}  \end{itemize}
813  %  %
814    \item [$<$MODE$>$]
815    %
816  \begin{itemize}  \begin{itemize}
817  %  %
818  \item {\tt -toplevel <S/R name>} \\  \item {\tt ad} generates the adjoint model (ADM)
819  Name of the toplevel routine, with respect to which the  \item {\tt ftl} generates the tangent linear model (TLM)
820  control flow analysis is performed.  \item {\tt svd} generates both ADM and TLM for \\
821  %  singular value decomposition (SVD) type calculations
 \item {\tt -input <variable names>} \\  
 List of independent variables $ u $ with respect to which the  
 dependent variable $ J $ is differentiated.  
 %  
 \item {\tt -output <variable name>} \\  
 Dependent variable $ J $  which is to be differentiated.  
 %  
 \item {\tt -reverse <file names>} \\  
 Adjoint code is generated to compute the sensitivity of an  
 independent variable w.r.t.  many dependent variables.  
 In the discussion of Section ???  
 the generated adjoint top-level routine computes the product  
 of the transposed Jacobian matrix $ M^T $ times  
 the gradient vector $ \nabla_v J $.  
 \\  
 {\tt <file names>} refers to the list of files {\it .f} which are to be  
 analyzed by TAMC. This list is generally smaller than the full list  
 of code to be compiled. The files not contained are either  
 above the top-level routine (some initializations), or are  
 deliberately hidden from TAMC, either because hand-written  
 adjoint routines exist, or the routines must not (or don't have to)  
 be differentiated. For each routine which is part of the flow tree  
 of the top-level routine, but deliberately hidden from TAMC  
 (or for each package which contains such routines),  
 a corresponding file {\it .flow} exists containing flow directives  
 for TAMC.  
822  %  %
823  \item {\tt -r4} \\  \end{itemize}
 ~  
824  %  %
825  \end{itemize}  \end{itemize}
826    
827    For example, to generate the adjoint model using TAF after routines ({\tt .F})
828    or headers ({\tt .h}) have been modified, but without compilation,
829    type {\tt make adtaf};
830    or, to generate the tangent linear model using TAMC without
831    re-generating the input code, type {\tt make ftltamconly}.
832    
 \subsubsection{The input parameter files}  
   
 \paragraph{File {\it data}}  
   
 \paragraph{File {\it data.cost}}  
   
 \paragraph{File {\it data.ctrl}}  
   
 \paragraph{File {\it data.gmredi}}  
   
 \paragraph{File {\it data.grdchk}}  
   
 \paragraph{File {\it data.optim}}  
   
 \paragraph{File {\it data.pkg}}  
   
 \paragraph{File {\it eedata}}  
   
 \paragraph{File {\it topog.bin}}  
   
 \paragraph{File {\it windx.bin, windy.bin}}  
833    
834  \paragraph{File {\it salt.bin, theta.bin}}  A typical full build process to generate the ADM via TAF would
835    look like follows:
836  \paragraph{File {\it SSS.bin, SST.bin}}  \begin{verbatim}
837    % mkdir build
838  \paragraph{File {\it pickup*}}  % cd build
839    % ../../../tools/genmake2 -mods=../code_ad
840  \subsection{Compiling the model and its adjoint}  % make depend
841    % make adall
842    \end{verbatim}
843    
844  The built process of the adjoint model is slightly more  %------------------------------------------------------------------
 complex than that of compiling the forward code.  
 The main reason is that the adjoint code generation requires  
 a specific list of routines that are to be differentiated  
 (as opposed to the automatic generation of a list of  
 files to be compiled by genmake).  
 This list excludes routines that don't have to be or must not be  
 differentiated. For some of the latter routines flow directives  
 may be necessary, a list of which has to be given as well.  
 For this reason, a separate {\it makefile} is currently  
 maintained in the directory {\tt adjoint/}. This  
 makefile is responsible for the adjoint code generation.  
845    
846  In the following we describe the build process step by step,  \subsection{The AD build process in detail
847  assuming you are in the directory {\tt bin/}.  \label{section_ad_build_detail}}
 A summary of steps to follow is given at the end.  
848    
849  \paragraph{Adjoint code generation and compilation -- step by step}  The {\tt make <MODE>all} target consists of the following procedures:
850    
851  \begin{enumerate}  \begin{enumerate}
852  %  %
853  \item  \item
854  {\tt ln -s ../verification/???/code/.genmakerc .} \\  A header file {\tt AD\_CONFIG.h} is generated which contains a CPP option
855  {\tt ln -s ../verification/???/code/*.[Fh] .} \\  on which code ought to be generated. Depending on the {\tt make} target,
856  Link your customized genmake options, header files,  the contents is
857  and modified code to the compile directory.  \begin{itemize}
 %  
858  \item  \item
859  {\tt ../tools/genmake -makefile} \\  {\tt \#define ALLOW\_ADJOINT\_RUN}
 Generate your Makefile (cf. Section ???).  
 %  
860  \item  \item
861  {\tt make depend} \\  {\tt \#define ALLOW\_TANGENTLINEAR\_RUN}
 Dependency analysis for the CPP pre-compiler (cf. Section ???).  
 %  
862  \item  \item
863  {\tt make small\_f} \\  {\tt \#define ALLOW\_ECCO\_OPTIMIZATION}
864  This is the first difference between forward code compilation  \end{itemize}
 and adjoint code generation and compilation.  
 Instead of going through the entire compilation process  
 (CPP precompiling -- {\tt .f}, object code generation -- {\tt .o},  
 linking of object files and libraries to generate executable),  
 only the CPP compiler is invoked at this stage to generate  
 the {\tt .f} files.  
865  %  %
866  \item  \item
867  {\tt cd ../adjoint} \\  A single file {\tt <MODE>\_input\_code.f} is concatenated
868  {\tt make adtaf} or {\tt make adtamc} \\  consisting of all {\tt .f} files that are part of the list {\bf AD\_FILES}
869  Depending on whether you have TAF or TAMC at your disposal,  and all {\tt .flow} files that are part of the list {\bf AD\_FLOW\_FILES}.
 you'll choose {\tt adtaf} or {\tt adtamc} as your  
 make target for the {\it makefile} in the directory {\tt adjoint/}.  
 Several things happen at this stage.  
 %  
 \begin{enumerate}  
870  %  %
871  \item  \item
872  The initial template file {\it adjoint\_model.F} which is part  The AD tool is invoked with the {\bf <MODE>\_<TOOL>\_FLAGS}.
873  of the compiling list created by {\it genmake} is restored.  The default AD tool flags in {\tt genmake2} can be overrwritten by
874    an {\tt adjoint\_options} file (similar to the platform-specific
875    {\tt build\_options}, see Section ???.
876    The AD tool writes the resulting AD code into the file
877    {\tt <MODE>\_input\_code\_ad.f}
878  %  %
879  \item  \item
880  All Fortran routines {\tt *.f} in {\tt bin/} are  A short sed script {\tt adjoint\_sed} is applied to
881  concatenated into a single file (it's current name is  {\tt <MODE>\_input\_code\_ad.f}
882  {\it tamc\_code.f}).  to reinstate {\bf myThid} into the CALL argument list of active file I/O.
883    The result is written to file {\tt <MODE>\_<TOOL>\_output.f}.
884  %  %
885  \item  \item
886  Adjoint code is generated by TAMC or TAF.  All routines are compiled and an executable is generated
887  The adjoint code is written to the file {\it tamc\_code\_ad.f}.  (see Table ???).
 It contains all adjoint routines of the forward routines  
 concatenated in {\it tamc\_code.f}.  
 For a given forward routines {\tt subroutine routinename}  
 the adjoint routine is named {\tt adsubroutine routinename}  
 by default (that default can be changed via the flag  
 {\tt -admark <markname>}).  
 Furthermore, it may contain modified code which  
 incorporates the translation of adjoint store directives  
 into specific Fortran code.  
 For a given forward routines {\tt subroutine routinename}  
 the modified routine is named {\tt mdsubroutine routinename}.  
 TAMC or TAF info is written to file  
 {\it tamc\_code.prot} or {\it taf.log}, respectively.  
888  %  %
889  \end{enumerate}  \end{enumerate}
890    
891    \subsubsection{The list AD\_FILES and {\tt .list} files}
892    
893    Not all routines are presented to the AD tool.
894    Routines typically hidden are diagnostics routines which
895    do not influence the cost function, but may create
896    artificial flow dependencies such as I/O of active variables.
897    
898    {\tt genmake2} generates a list (or variable) {\bf AD\_FILES}
899    which contains all routines that are shown to the AD tool.
900    This list is put together from all files with suffix {\tt .list}
901    that {\tt genmake2} finds in its search directories.
902    The list file for the core MITgcm routines is in {\tt model/src/}
903    is called {\tt model\_ad\_diff.list}.
904    Note that no wrapper routine is shown to TAF. These are either
905    not visible at all to the AD code, or hand-written AD code
906    is available (see next section).
907    
908    Each package directory contains its package-specific
909    list file {\tt <PKG>\_ad\_diff.list}. For example,
910    {\tt pkg/ptracers/} contains the file {\tt ptracers\_ad\_diff.list}.
911    Thus, enabling a package will automatically extend the
912    {\bf AD\_FILES} list of {\tt genmake2} to incorporate the
913    package-specific routines.
914    Note that you will need to regenerate the {\tt Makefile} if
915    you enable a package (e.g. by adding it to {\tt packages.conf})
916    and a {\tt Makefile} already exists.
917    
918    \subsubsection{The list AD\_FLOW\_FILES and {\tt .flow} files}
919    
920    TAMC and TAF can evaluate user-specified directives
921    that start with a specific syntax ({\tt CADJ}, {\tt C\$TAF}, {\tt !\$TAF}).
922    The main categories of directives are STORE directives and
923    FLOW directives. Here, we are concerned with flow directives,
924    store directives are treated elsewhere.
925    
926    Flow directives enable the AD tool to evaluate how it should treat
927    routines that are 'hidden' by the user, i.e. routines which are
928    not contained in the {\bf AD\_FILES} list (see previous section),
929    but which are called in part of the code that the AD tool does see.
930    The flow directive tell the AD tool
931  %  %
932  \item  \begin{itemize}
 {\tt make adchange} \\  
 The multi-threading capability of the MITGCM requires a slight  
 change in the parameter list of some routines that are related to  
 to active file handling.  
 This post-processing invokes the sed script {\it adjoint\_ecco\_sed.com}  
 to insert the threading counter {\bf myThId} into the parameter list  
 of those subroutines.  
 The resulting code is written to file {\it tamc\_code\_sed\_ad.f}  
 and appended to the file {\it adjoint\_model.F}.  
 This concludes the adjoint code generation.  
933  %  %
934  \item  \item which subroutine arguments are input/output
935  {\tt cd ../bin} \\  \item which subroutine arguments are active
936  {\tt make} \\  \item which subroutine arguments are required to compute the cost
937  The file {\it adjoint\_model.F} now contains the full adjoint code.  \item which subroutine arguments are dependent
 All routines are now compiled.  
938  %  %
939  \end{enumerate}  \end{itemize}
940    %
941    The syntax for the flow directives can be found in the
942    AD tool manuals.
943    
944  \paragraph{Adjoint code generation and compilation -- summary}  {\tt genmake2} generates a list (or variable) {\bf AD\_FLOW\_FILES}
945  ~ \\  which contains all files with suffix{\tt .flow} that it finds
946    in its search directories.
947    The flow directives for the core MITgcm routines of
948    {\tt eesupp/src/} and {\tt model/src/}
949    reside in {\tt pkg/autodiff/}.
950    This directory also contains hand-written adjoint code
951    for the MITgcm WRAPPER (section \ref{chap:sarch}).
952    
953    Flow directives for package-specific routines are contained in
954    the corresponding package directories in the file
955    {\tt <PKG>\_ad.flow}, e.g. ptracers-specific directives are in
956    {\tt ptracers\_ad.flow}.
957    
958    \subsubsection{Store directives for 3-level checkpointing}
959    
960    The storing that is required at each period of the
961    3-level checkpointing is controled by three
962    top-level headers.
963    
964  \[  \begin{verbatim}
965  \boxed{  do ilev_3 = 1, nchklev_3
966  \begin{split}  #  include ``checkpoint_lev3.h''
967   ~ & \mbox{\tt cd bin} \\     do ilev_2 = 1, nchklev_2
968   ~ & \mbox{\tt ln -s ../verification/my\_experiment/code/.genmakerc .} \\  #     include ``checkpoint_lev2.h''
969   ~ & \mbox{\tt ln -s ../verification/my\_experiment/code/*.[Fh] .} \\        do ilev_1 = 1, nchklev_1
970   ~ & \mbox{\tt ../tools/genmake -makefile} \\  #        include ``checkpoint_lev1.h''
971   ~ & \mbox{\tt make depend} \\  
972   ~ & \mbox{\tt make small\_f} \\  ...
973   ~ & \mbox{\tt cd ../adjoint} \\  
974   ~ & \mbox{\tt make adtaf <OR: make adtamc>} \\        end do
975   ~ & \mbox{\tt make adchange} \\     end do
976   ~ & \mbox{\tt cd ../bin} \\  end do
977   ~ & \mbox{\tt make} \\  \end{verbatim}
 \end{split}  
 }  
 \]  
978    
979  \newpage  All files {\tt checkpoint\_lev?.h} are contained in directory
980    {\tt pkg/autodiff/}.
981    
 %**********************************************************************  
 \section{TLM and ADM generation in general}  
 \label{sec_ad_setup_gen}  
 %**********************************************************************  
982    
983  In this section we describe in a general fashion  \subsubsection{Changing the default AD tool flags: ad\_options files}
 the parts of the code that are relevant for automatic  
 differentiation using the software tool TAMC.  
984    
 \begin{figure}[b!]  
 \input{part5/doc_ad_the_model}  
 \caption{~}  
 \label{fig:adthemodel}  
 \end{figure}  
985    
986  The basic flow is depicted in \ref{fig:adthemodel}.  \subsubsection{Hand-written adjoint code}
987  If the option {\tt ALLOW\_AUTODIFF\_TAMC} is defined, the driver routine  
988  {\it the\_model\_main}, instead of calling {\it the\_main\_loop},  %------------------------------------------------------------------
 invokes the adjoint of this routine, {\it adthe\_main\_loop},  
 which is the toplevel routine in terms of reverse mode computation.  
 The routine {\it adthe\_main\_loop} has been generated using TAMC.  
 It contains both the forward integration of the full model,  
 any additional storing that is required for efficient checkpointing,  
 and the reverse integration of the adjoint model.  
 The structure of {\it adthe\_main\_loop} has been strongly  
 simplified for clarification; in particular, no checkpointing  
 procedures are shown here.  
 Prior to the call of {\it adthe\_main\_loop}, the routine  
 {\it ctrl\_unpack} is invoked to unpack the control vector,  
 and following that call, the routine {\it ctrl\_pack}  
 is invoked to pack the control vector  
 (cf. Section \ref{section_ctrl}).  
 If gradient checks are to be performed, the option  
 {\tt ALLOW\_GRADIENT\_CHECK} is defined. In this case  
 the driver routine {\it grdchk\_main} is called after  
 the gradient has been computed via the adjoint  
 (cf. Section \ref{section_grdchk}).  
989    
990  \subsection{The cost function (dependent variable)  \subsection{The cost function (dependent variable)
991  \label{section_cost}}  \label{section_cost}}
# Line 1293  the gradient has been computed via the a Line 993  the gradient has been computed via the a
993  The cost function $ {\cal J} $ is referred to as the {\sf dependent variable}.  The cost function $ {\cal J} $ is referred to as the {\sf dependent variable}.
994  It is a function of the input variables $ \vec{u} $ via the composition  It is a function of the input variables $ \vec{u} $ via the composition
995  $ {\cal J}(\vec{u}) \, = \, {\cal J}(M(\vec{u})) $.  $ {\cal J}(\vec{u}) \, = \, {\cal J}(M(\vec{u})) $.
996  The input is referred to as the  The input are referred to as the
997  {\sf independent variables} or {\sf control variables}.  {\sf independent variables} or {\sf control variables}.
998  All aspects relevant to the treatment of the cost function $ {\cal J} $  All aspects relevant to the treatment of the cost function $ {\cal J} $
999  (parameter setting, initialization, accumulation,  (parameter setting, initialization, accumulation,
1000  final evaluation), are controlled by the package {\it pkg/cost}.  final evaluation), are controlled by the package {\it pkg/cost}.
1001    The aspects relevant to the treatment of the independent variables
1002    are controlled by the package {\it pkg/ctrl} and will be treated
1003    in the next section.
1004    
 \begin{figure}[h!]  
1005  \input{part5/doc_cost_flow}  \input{part5/doc_cost_flow}
 \caption{~}  
 \label{fig:costflow}  
 \end{figure}  
1006    
1007  \subsubsection{genmake and CPP options}  \subsubsection{Enabling the package}
1008  %  
 \begin{itemize}  
 %  
 \item  
1009  \fbox{  \fbox{
1010  \begin{minipage}{12cm}  \begin{minipage}{12cm}
1011  {\it genmake}, {\it CPP\_OPTIONS.h}, {\it ECCO\_CPPOPTIONS.h}  {\it packages.conf}, {\it ECCO\_CPPOPTIONS.h}
1012  \end{minipage}  \end{minipage}
1013  }  }
1014  \end{itemize}  \begin{itemize}
 %  
 The directory {\it pkg/cost} can be included to the  
 compile list in 3 different ways (cf. Section \ref{???}):  
1015  %  %
1016  \begin{enumerate}  \item
1017    The package is enabled by adding {\it cost} to your file {\it packages.conf}
1018    (see Section ???)
1019  %  %
1020  \item {\it genmake}: \\  \item
1021  Change the default settings in the file {\it genmake} by adding  
1022  {\bf cost} to the {\bf enable} list (not recommended).  
1023  %  \end{itemize}
 \item {\it .genmakerc}: \\  
 Customize the settings of {\bf enable}, {\bf disable} which are  
 appropriate for your experiment in the file {\it .genmakerc}  
 and add the file to your compile directory.  
 %  
 \item genmake-options: \\  
 Call {\it genmake} with the option  
 {\tt genmake -enable=cost}.  
1024  %  %
1025  \end{enumerate}  
1026    N.B.: In general the following packages ought to be enabled
1027    simultaneously: {\it autodiff, cost, ctrl}.
1028  The basic CPP option to enable the cost function is {\bf ALLOW\_COST}.  The basic CPP option to enable the cost function is {\bf ALLOW\_COST}.
1029  Each specific cost function contribution has its own option.  Each specific cost function contribution has its own option.
1030  For the present example the option is {\bf ALLOW\_COST\_TRACER}.  For the present example the option is {\bf ALLOW\_COST\_TRACER}.
1031  All cost-specific options are set in {\it ECCO\_CPPOPTIONS.h}  All cost-specific options are set in {\it ECCO\_CPPOPTIONS.h}
1032  Since the cost function is usually used in conjunction with  Since the cost function is usually used in conjunction with
1033  automatic differentiation, the CPP option  automatic differentiation, the CPP option
1034  {\bf ALLOW\_ADJOINT\_RUN} should be defined  {\bf ALLOW\_ADJOINT\_RUN} (file {\it CPP\_OPTIONS.h}) and
1035  (file {\it CPP\_OPTIONS.h}).  {\bf ALLOW\_AUTODIFF\_TAMC} (file {\it ECCO\_CPPOPTIONS.h})
1036    should be defined.
1037    
1038  \subsubsection{Initialization}  \subsubsection{Initialization}
1039  %  %
1040  The initialization of the {\it cost} package is readily enabled  The initialization of the {\it cost} package is readily enabled
1041  as soon as the CPP option {\bf ALLOW\_ADJOINT\_RUN} is defined.  as soon as the CPP option {\bf ALLOW\_COST} is defined.
1042  %  %
1043  \begin{itemize}  \begin{itemize}
1044  %  %
# Line 1422  from each contribution and sums over all Line 1112  from each contribution and sums over all
1112  \begin{equation}  \begin{equation}
1113  {\cal J} \, = \,  {\cal J} \, = \,
1114  {\rm fc} \, = \,  {\rm fc} \, = \,
1115  {\rm mult\_tracer} \sum_{bi,\,bj}^{nSx,\,nSy}  {\rm mult\_tracer} \sum_{\text{global sum}} \sum_{bi,\,bj}^{nSx,\,nSy}
1116  {\rm objf\_tracer}(bi,bj) \, + \, ...  {\rm objf\_tracer}(bi,bj) \, + \, ...
1117  \end{equation}  \end{equation}
1118  %  %
# Line 1434  tamc -output 'fc' ... Line 1124  tamc -output 'fc' ...
1124    
1125  %%%% \end{document}  %%%% \end{document}
1126    
 \begin{figure}  
1127  \input{part5/doc_ad_the_main}  \input{part5/doc_ad_the_main}
 \caption{~}  
 \label{fig:adthemain}  
 \end{figure}  
1128    
1129  \subsection{The control variables (independent variables)  \subsection{The control variables (independent variables)
1130  \label{section_ctrl}}  \label{section_ctrl}}
# Line 1458  All aspects relevant to the treatment of Line 1144  All aspects relevant to the treatment of
1144  (parameter setting, initialization, perturbation)  (parameter setting, initialization, perturbation)
1145  are controlled by the package {\it pkg/ctrl}.  are controlled by the package {\it pkg/ctrl}.
1146    
 \begin{figure}[h!]  
1147  \input{part5/doc_ctrl_flow}  \input{part5/doc_ctrl_flow}
 \caption{~}  
 \label{fig:ctrlflow}  
 \end{figure}  
1148    
1149  \subsubsection{genmake and CPP options}  \subsubsection{genmake and CPP options}
1150  %  %
# Line 1478  are controlled by the package {\it pkg/c Line 1160  are controlled by the package {\it pkg/c
1160  %  %
1161  To enable the directory to be included to the compile list,  To enable the directory to be included to the compile list,
1162  {\bf ctrl} has to be added to the {\bf enable} list in  {\bf ctrl} has to be added to the {\bf enable} list in
1163  {\it .genmakerc} (or {\it genmake} itself).  {\it .genmakerc} or in {\it genmake} itself (analogous to {\it cost}
1164    package, cf. previous section).
1165  Each control variable is enabled via its own CPP option  Each control variable is enabled via its own CPP option
1166  in {\it ECCO\_CPPOPTIONS.h}.  in {\it ECCO\_CPPOPTIONS.h}.
1167    
# Line 1519  and their gradients: {\it ctrl\_unpack} Line 1202  and their gradients: {\it ctrl\_unpack}
1202  \\  \\
1203  %  %
1204  Two important issues related to the handling of the control  Two important issues related to the handling of the control
1205  variables in the MITGCM need to be addressed.  variables in MITgcm need to be addressed.
1206  First, in order to save memory, the control variable arrays  First, in order to save memory, the control variable arrays
1207  are not kept in memory, but rather read from file and added  are not kept in memory, but rather read from file and added
1208  to the initial fields during the model initialization phase.  to the initial fields during the model initialization phase.
# Line 1594  when calling TAMC: Line 1277  when calling TAMC:
1277  tamc -input 'xx_tr1 ...' ...  tamc -input 'xx_tr1 ...' ...
1278  \end{verbatim}  \end{verbatim}
1279  %  %
1280  Now, as mentioned above, the MITGCM avoids maintaining  Now, as mentioned above, MITgcm avoids maintaining
1281  an array for each control variable by reading the  an array for each control variable by reading the
1282  perturbation to a temporary array from file.  perturbation to a temporary array from file.
1283  To ensure the symbolic link to be recognized by TAMC, a scalar  To ensure the symbolic link to be recognized by TAMC, a scalar
# Line 1622  in the code takes on the form Line 1305  in the code takes on the form
1305  %  %
1306  Note, that reading an active variable corresponds  Note, that reading an active variable corresponds
1307  to a variable assignment. Its derivative corresponds  to a variable assignment. Its derivative corresponds
1308  to a write statement of the adjoint variable.  to a write statement of the adjoint variable, followed by
1309    a reset.
1310  The 'active file' routines have been designed  The 'active file' routines have been designed
1311  to support active read and corresponding adjoint active write  to support active read and corresponding adjoint active write
1312  operations (and vice versa).  operations (and vice versa).
# Line 1739  at intermediate times can be written usi Line 1423  at intermediate times can be written usi
1423  {\it addummy\_in\_stepping}.  {\it addummy\_in\_stepping}.
1424  This routine is part of the adjoint support package  This routine is part of the adjoint support package
1425  {\it pkg/autodiff} (cf.f. below).  {\it pkg/autodiff} (cf.f. below).
1426    The procedure is enabled using via the CPP-option
1427    {\bf ALLOW\_AUTODIFF\_MONITOR} (file {\it ECCO\_CPPOPTIONS.h}).
1428  To be part of the adjoint code, the corresponding S/R  To be part of the adjoint code, the corresponding S/R
1429  {\it dummy\_in\_stepping} has to be called in the forward  {\it dummy\_in\_stepping} has to be called in the forward
1430  model (S/R {\it the\_main\_loop}) at the appropriate place.  model (S/R {\it the\_main\_loop}) at the appropriate place.
1431    The adjoint common blocks are extracted from the adjoint code
1432    via the header file {\it adcommon.h}.
1433    
1434  {\it dummy\_in\_stepping} is essentially empty,  {\it dummy\_in\_stepping} is essentially empty,
1435  the corresponding adjoint routine is hand-written rather  the corresponding adjoint routine is hand-written rather
# Line 1768  the common blocks Line 1456  the common blocks
1456  {\bf /adtr1\_r/}, {\bf /adffields/},  {\bf /adtr1\_r/}, {\bf /adffields/},
1457  which have been extracted from the adjoint code to enable  which have been extracted from the adjoint code to enable
1458  access to the adjoint variables.  access to the adjoint variables.
1459    
1460    {\bf WARNING:} If the structure of the common blocks
1461    {\bf /dynvars\_r/}, {\bf /dynvars\_cd/}, etc., changes
1462    similar changes will occur in the adjoint common blocks.
1463    Therefore, consistency between the TAMC-generated common blocks
1464    and those in {\it adcommon.h} have to be checked.
1465  %  %
1466  \end{itemize}  \end{itemize}
1467    
# Line 1782  The gradient $ \nabla _{u}{\cal J} |_{u_ Line 1476  The gradient $ \nabla _{u}{\cal J} |_{u_
1476  with the value of the cost function itself $ {\cal J}(u_{[k]}) $  with the value of the cost function itself $ {\cal J}(u_{[k]}) $
1477  at iteration step $ k $ serve  at iteration step $ k $ serve
1478  as input to a minimization routine (e.g. quasi-Newton method,  as input to a minimization routine (e.g. quasi-Newton method,
1479  conjugate gradient, ... \cite{gil_lem:89})  conjugate gradient, ... \cite{gil-lem:89})
1480  to compute an update in the  to compute an update in the
1481  control variable for iteration step $k+1$  control variable for iteration step $k+1$
1482  \[  \[
# Line 1913  to {\it adxx\_...$<$k$>$}, again via the Line 1607  to {\it adxx\_...$<$k$>$}, again via the
1607  Finally, {\it ctrl\_pack} collects all adjoint files  Finally, {\it ctrl\_pack} collects all adjoint files
1608  and writes them to the compressed vector file  and writes them to the compressed vector file
1609  {\bf vector\_grad\_$<$k$>$}.  {\bf vector\_grad\_$<$k$>$}.
   
 \subsection{TLM and ADM generation via TAMC}  
   
   
   
 \subsection{Flow directives and adjoint support routines \label{section_flowdir}}  
   
 \subsection{Store directives and checkpointing \label{section_checkpointing}}  
   
 \subsection{Gradient checks \label{section_grdchk}}  
   
 \subsection{Second derivative generation via TAMC}  
   
 \section{Example of adjoint code}  

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