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revision 1.7 by cnh, Thu Oct 25 18:36:55 2001 UTC revision 1.24 by jmc, Tue Aug 31 20:56:21 2010 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
14  they parse a program code as input and produce a new program code  (we restrict our discussion to source-to-source tools, ignoring
15  as output.  operator-overloading tools).  However, unlike a
16  However, unlike a pure source-to-source translation, the output program  pure source-to-source translation, the output program represents a new
17  represents a new algorithm, such as the evaluation of the  algorithm, such as the evaluation of the Jacobian, the Hessian, or
18  Jacobian, the Hessian, or higher derivative operators.  higher derivative operators.  In principle, a variety of derived
19  In principle, a variety of derived algorithms  algorithms can be generated automatically in this way.
20  can be generated automatically in this way.  
21    MITgcm has been adapted for use with the Tangent linear and Adjoint
22  The MITGCM has been adapted for use with the  Model Compiler (TAMC) and its successor TAF (Transformation of
23  Tangent linear and Adjoint Model Compiler (TAMC) and its successor TAF  Algorithms in Fortran), developed by Ralf Giering (\cite{gie-kam:98},
24  (Transformation of Algorithms in Fortran), developed  \cite{gie:99,gie:00}).  The first application of the adjoint of MITgcm
25  by Ralf Giering (\cite{gie-kam:98}, \cite{gie:99,gie:00}).  for sensitivity studies has been published by \cite{maro-eta:99}.
26  The first application of the adjoint of the MITGCM for sensitivity  \cite{stam-etal:97,stam-etal:02} use MITgcm and its adjoint for ocean
27  studies has been published by \cite{maro-eta:99}.  state estimation studies.  In the following we shall refer to TAMC and
28  \cite{sta-eta:97,sta-eta:01} use the MITGCM and its adjoint  TAF synonymously, except were explicitly stated otherwise.
29  for ocean state estimation studies.  
30  In the following we shall refer to TAMC and TAF synonymously,  As of mid-2007 we are also able to generate fairly efficient
31  except were explicitly stated otherwise.  adjoint code of the MITgcm using a new, open-source AD tool,
32    called OpenAD (see \cite{naum-etal:06,utke-etal:08}.
33  TAMC exploits the chain rule for computing the first  This enables us for the first time to compare adjoint models
34  derivative of a function with  generated from different AD tools, providing an additional
35  respect to a set of input variables.  accuracy check, complementary to finite-difference gradient checks.
36  Treating a given forward code as a composition of operations --  OpenAD and its application to  MITgcm is described in detail
37  each line representing a compositional element, the chain rule is  in section \ref{sec_ad_openad}.
38  rigorously applied to the code, line by line. The resulting  
39  tangent linear or adjoint code,  The AD tool exploits the chain rule for computing the first derivative of a
40  then, may be thought of as the composition in  function with respect to a set of input variables.  Treating a given
41  forward or reverse order, respectively, of the  forward code as a composition of operations -- each line representing
42  Jacobian matrices of the forward code's compositional elements.  a compositional element, the chain rule is rigorously applied to the
43    code, line by line. The resulting tangent linear or adjoint code,
44    then, may be thought of as the composition in forward or reverse
45    order, respectively, of the Jacobian matrices of the forward code's
46    compositional elements.
47    
48  %**********************************************************************  %**********************************************************************
49  \section{Some basic algebra}  \section{Some basic algebra}
50  \label{sec_ad_algebra}  \label{sec_ad_algebra}
51    \begin{rawhtml}
52    <!-- CMIREDIR:sec_ad_algebra: -->
53    \end{rawhtml}
54  %**********************************************************************  %**********************************************************************
55    
56  Let $ \cal{M} $ be a general nonlinear, model, i.e. a  Let $ \cal{M} $ be a general nonlinear, model, i.e. a
# Line 56  model output variable $\vec{v}=(v_1,\ldo Line 65  model output variable $\vec{v}=(v_1,\ldo
65  under consideration,  under consideration,
66  %  %
67  \begin{equation}  \begin{equation}
68  \begin{split}  \begin{aligned}
69  {\cal M} \, : & \, U \,\, \longrightarrow \, V \\  {\cal M} \, : & \, U \,\, \longrightarrow \, V \\
70  ~      & \, \vec{u} \,\, \longmapsto \, \vec{v} \, = \,  ~      & \, \vec{u} \,\, \longmapsto \, \vec{v} \, = \,
71  {\cal M}(\vec{u})  {\cal M}(\vec{u})
72  \label{fulloperator}  \label{fulloperator}
73  \end{split}  \end{aligned}
74  \end{equation}  \end{equation}
75  %  %
76  The vectors $ \vec{u} \in U $ and $ v \in V $ may be represented w.r.t.  The vectors $ \vec{u} \in U $ and $ v \in V $ may be represented w.r.t.
# Line 141  w.r.t. their corresponding inner product Line 150  w.r.t. their corresponding inner product
150  $\left\langle \,\, , \,\, \right\rangle $  $\left\langle \,\, , \,\, \right\rangle $
151  %  %
152  \begin{equation}  \begin{equation}
153  \begin{split}  \begin{aligned}
154  {\cal J} & = \,  {\cal J} & = \,
155  {\cal J} |_{\vec{u}^{(0)}} \, + \,  {\cal J} |_{\vec{u}^{(0)}} \, + \,
156  \left\langle \, \nabla _{u}{\cal J}^T |_{\vec{u}^{(0)}} \, , \, \delta \vec{u} \, \right\rangle  \left\langle \, \nabla _{u}{\cal J}^T |_{\vec{u}^{(0)}} \, , \, \delta \vec{u} \, \right\rangle
# Line 150  $\left\langle \,\, , \,\, \right\rangle Line 159  $\left\langle \,\, , \,\, \right\rangle
159  {\cal J} |_{\vec{v}^{(0)}} \, + \,  {\cal J} |_{\vec{v}^{(0)}} \, + \,
160  \left\langle \, \nabla _{v}{\cal J}^T |_{\vec{v}^{(0)}} \, , \, \delta \vec{v} \, \right\rangle  \left\langle \, \nabla _{v}{\cal J}^T |_{\vec{v}^{(0)}} \, , \, \delta \vec{v} \, \right\rangle
161  \, + \, O(\delta \vec{v}^2)  \, + \, O(\delta \vec{v}^2)
162  \end{split}  \end{aligned}
163  \label{deljidentity}  \label{deljidentity}
164  \end{equation}  \end{equation}
165  %  %
# Line 191  the gradient $ \nabla _{u}{\cal J} $ can Line 200  the gradient $ \nabla _{u}{\cal J} $ can
200  invoking the adjoint $ M^{\ast } $ of the tangent linear model $ M $  invoking the adjoint $ M^{\ast } $ of the tangent linear model $ M $
201  %  %
202  \begin{equation}  \begin{equation}
203  \begin{split}  \begin{aligned}
204  \nabla _{u}{\cal J}^T |_{\vec{u}} &  \nabla _{u}{\cal J}^T |_{\vec{u}} &
205  = \, M^T |_{\vec{u}} \cdot \nabla _{v}{\cal J}^T |_{\vec{v}}  \\  = \, M^T |_{\vec{u}} \cdot \nabla _{v}{\cal J}^T |_{\vec{v}}  \\
206  ~ & = \, M^T |_{\vec{u}} \cdot \delta \vec{v}^{\ast} \\  ~ & = \, M^T |_{\vec{u}} \cdot \delta \vec{v}^{\ast} \\
207  ~ & = \, \delta \vec{u}^{\ast}  ~ & = \, \delta \vec{u}^{\ast}
208  \end{split}  \end{aligned}
209  \label{adjoint}  \label{adjoint}
210  \end{equation}  \end{equation}
211  %  %
# Line 244  $ \langle \, \nabla _{v}{\cal J}^T \, , Line 253  $ \langle \, \nabla _{v}{\cal J}^T \, ,
253  = \nabla_v {\cal J} \cdot \delta \vec{v} $ )  = \nabla_v {\cal J} \cdot \delta \vec{v} $ )
254  %  %
255  \begin{equation}  \begin{equation}
256  \begin{split}  \begin{aligned}
257  \nabla_v {\cal J} (M(\delta \vec{u})) & = \,  \nabla_v {\cal J} (M(\delta \vec{u})) & = \,
258  \nabla_v {\cal J} \cdot M_{\Lambda}  \nabla_v {\cal J} \cdot M_{\Lambda}
259  \cdot ...... \cdot M_{\lambda} \cdot ...... \cdot  \cdot ...... \cdot M_{\lambda} \cdot ...... \cdot
260  M_{1} \cdot M_{0} \cdot \delta \vec{u} \\  M_{1} \cdot M_{0} \cdot \delta \vec{u} \\
261  ~ & = \, \nabla_v {\cal J} \cdot \delta \vec{v} \\  ~ & = \, \nabla_v {\cal J} \cdot \delta \vec{v} \\
262  \end{split}  \end{aligned}
263  \label{forward}  \label{forward}
264  \end{equation}  \end{equation}
265  %  %
# Line 258  whereas in reverse mode we have Line 267  whereas in reverse mode we have
267  %  %
268  \begin{equation}  \begin{equation}
269  \boxed{  \boxed{
270  \begin{split}  \begin{aligned}
271  M^T ( \nabla_v {\cal J}^T) & = \,  M^T ( \nabla_v {\cal J}^T) & = \,
272  M_{0}^T \cdot M_{1}^T  M_{0}^T \cdot M_{1}^T
273  \cdot ...... \cdot M_{\lambda}^T \cdot ...... \cdot  \cdot ...... \cdot M_{\lambda}^T \cdot ...... \cdot
# Line 267  M_{\Lambda}^T \cdot \nabla_v {\cal J}^T Line 276  M_{\Lambda}^T \cdot \nabla_v {\cal J}^T
276  \cdot ...... \cdot  \cdot ...... \cdot
277  \nabla_{v^{(\lambda)}} {\cal J}^T \\  \nabla_{v^{(\lambda)}} {\cal J}^T \\
278  ~ & = \, \nabla_u {\cal J}^T  ~ & = \, \nabla_u {\cal J}^T
279  \end{split}  \end{aligned}
280  }  }
281  \label{reverse}  \label{reverse}
282  \end{equation}  \end{equation}
# Line 286  $ \vec{v}^{(\lambda)} $ at each intermed Line 295  $ \vec{v}^{(\lambda)} $ at each intermed
295  %  %
296  \begin{equation}  \begin{equation}
297  \boxed{  \boxed{
298  \begin{split}  \begin{aligned}
299  \nabla_{v^{(\lambda)}} {\cal J}^T |_{\vec{v}^{(\lambda)}}  \nabla_{v^{(\lambda)}} {\cal J}^T |_{\vec{v}^{(\lambda)}}
300  & = \,  & = \,
301  M_{\lambda}^T |_{\vec{v}^{(\lambda)}} \cdot ...... \cdot  M_{\lambda}^T |_{\vec{v}^{(\lambda)}} \cdot ...... \cdot
302  M_{\Lambda}^T |_{\vec{v}^{(\lambda)}} \cdot \delta \vec{v}^{\ast} \\  M_{\Lambda}^T |_{\vec{v}^{(\lambda)}} \cdot \delta \vec{v}^{\ast} \\
303  ~ & = \, \delta \vec{v}^{(\lambda) \, \ast}  ~ & = \, \delta \vec{v}^{(\lambda) \, \ast}
304  \end{split}  \end{aligned}
305  }  }
306  \end{equation}  \end{equation}
307  %  %
# Line 409  and the shorthand notation for the adjoi Line 418  and the shorthand notation for the adjoi
418  $ \delta v^{(\lambda) \, \ast}_{j} = \frac{\partial}{\partial v^{(\lambda)}_{j}}  $ \delta v^{(\lambda) \, \ast}_{j} = \frac{\partial}{\partial v^{(\lambda)}_{j}}
419  {\cal J}^T $, $ j = 1, \ldots , n_{\lambda} $,  {\cal J}^T $, $ j = 1, \ldots , n_{\lambda} $,
420  for intermediate components, yielding  for intermediate components, yielding
421    {\small
422  \begin{equation}  \begin{equation}
423  \small  \begin{aligned}
 \begin{split}  
424  \left(  \left(
425  \begin{array}{c}  \begin{array}{c}
426  \delta v^{(\lambda) \, \ast}_1 \\  \delta v^{(\lambda) \, \ast}_1 \\
# Line 456  for intermediate components, yielding Line 465  for intermediate components, yielding
465  \delta v^{\ast}_{n} \\  \delta v^{\ast}_{n} \\
466  \end{array}  \end{array}
467  \right)  \right)
468  \end{split}  \end{aligned}
469  \end{equation}  \end{equation}
470    }
471    
472  Eq. (\ref{forward}) and (\ref{reverse}) are perhaps clearest in  Eq. (\ref{forward}) and (\ref{reverse}) are perhaps clearest in
473  showing the advantage of the reverse over the forward mode  showing the advantage of the reverse over the forward mode
# Line 528  operator which maps the model state spac Line 538  operator which maps the model state spac
538  Then, $ \nabla_v {\cal J} $ takes the form  Then, $ \nabla_v {\cal J} $ takes the form
539  %  %
540  \begin{equation*}  \begin{equation*}
541  \begin{split}  \begin{aligned}
542  \nabla_v {\cal J}^T & = \, 2 \, \, H \cdot  \nabla_v {\cal J}^T & = \, 2 \, \, H \cdot
543  \left( \, {\cal H}(\vec{v}) - \vec{d} \, \right) \\  \left( \, {\cal H}(\vec{v}) - \vec{d} \, \right) \\
544  ~          & = \, 2 \sum_{j} \left\{ \sum_k  ~          & = \, 2 \sum_{j} \left\{ \sum_k
545  \frac{\partial {\cal H}_k}{\partial v_{j}}  \frac{\partial {\cal H}_k}{\partial v_{j}}
546  \left( {\cal H}_k (\vec{v}) - d_k \right)  \left( {\cal H}_k (\vec{v}) - d_k \right)
547  \right\} \, {\vec{f}_{j}} \\  \right\} \, {\vec{f}_{j}} \\
548  \end{split}  \end{aligned}
549  \end{equation*}  \end{equation*}
550  %  %
551  where $H_{kj} = \partial {\cal H}_k / \partial v_{j} $ is the  where $H_{kj} = \partial {\cal H}_k / \partial v_{j} $ is the
# Line 557  Because of the local character of the de Line 567  Because of the local character of the de
567  (a derivative is defined w.r.t. a point along the trajectory),  (a derivative is defined w.r.t. a point along the trajectory),
568  the intermediate results of the model trajectory  the intermediate results of the model trajectory
569  $\vec{v}^{(\lambda+1)}={\cal M}_{\lambda}(v^{(\lambda)})$  $\vec{v}^{(\lambda+1)}={\cal M}_{\lambda}(v^{(\lambda)})$
570  are needed to evaluate the intermediate Jacobian  may be required to evaluate the intermediate Jacobian
571  $M_{\lambda}|_{\vec{v}^{(\lambda)}} \, \delta \vec{v}^{(\lambda)} $.  $M_{\lambda}|_{\vec{v}^{(\lambda)}} \, \delta \vec{v}^{(\lambda)} $.
572    This is the case e.g. for nonlinear expressions
573    (momentum advection, nonlinear equation of state), state-dependent
574    conditional statements (parameterization schemes).
575  In the forward mode, the intermediate results are required  In the forward mode, the intermediate results are required
576  in the same order as computed by the full forward model ${\cal M}$,  in the same order as computed by the full forward model ${\cal M}$,
577  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 582  point of evaluation has to be recomputed
582    
583  A method to balance the amount of recomputations vs.  A method to balance the amount of recomputations vs.
584  storage requirements is called {\sf checkpointing}  storage requirements is called {\sf checkpointing}
585  (e.g. \cite{res-eta:98}).  (e.g. \cite{gri:92}, \cite{res-eta:98}).
586  It is depicted in \ref{fig:3levelcheck} for a 3-level checkpointing  It is depicted in \ref{fig:3levelcheck} for a 3-level checkpointing
587  [as an example, we give explicit numbers for a 3-day  [as an example, we give explicit numbers for a 3-day
588  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 593  In a first step, the model trajectory is
593  $ {n}^{lev3} $ subsections [$ {n}^{lev3} $=3 1-day intervals],  $ {n}^{lev3} $ subsections [$ {n}^{lev3} $=3 1-day intervals],
594  with the label $lev3$ for this outermost loop.  with the label $lev3$ for this outermost loop.
595  The model is then integrated along the full trajectory,  The model is then integrated along the full trajectory,
596  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
597  [i.e. 3 times, at  [i.e. 3 times, at
598  $ i = 0,1,2 $ corresponding to $ k_{i}^{lev3} = 0, 24, 48 $].  $ i = 0,1,2 $ corresponding to $ k_{i}^{lev3} = 0, 24, 48 $].
599    In addition, the cost function is computed, if needed.
600  %  %
601  \item [$lev2$]  \item [$lev2$]
602  In a second step each subsection itself is divided into  In a second step each subsection itself is divided into
603  $ {n}^{lev2} $ sub-subsections  $ {n}^{lev2} $ subsections
604  [$ {n}^{lev2} $=4 6-hour intervals per subsection].  [$ {n}^{lev2} $=4 6-hour intervals per subsection].
605  The model picks up at the last outermost dumped state  The model picks up at the last outermost dumped state
606  $ v_{k_{n}^{lev3}} $ and is integrated forward in time along  $ v_{k_{n}^{lev3}} $ and is integrated forward in time along
607  the last subsection, with the label $lev2$ for this    the last subsection, with the label $lev2$ for this  
608  intermediate loop.  intermediate loop.
609  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
610  timestep  timestep
611  [i.e. 4 times, at  [i.e. 4 times, at
612  $ 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 614  $ i = 0,1,2,3 $ corresponding to $ k_{i}
614  \item [$lev1$]  \item [$lev1$]
615  Finally, the model picks up at the last intermediate dump state  Finally, the model picks up at the last intermediate dump state
616  $ v_{k_{n}^{lev2}} $ and is integrated forward in time along  $ v_{k_{n}^{lev2}} $ and is integrated forward in time along
617  the last sub-subsection, with the label $lev1$ for this    the last subsection, with the label $lev1$ for this  
618  intermediate loop.  intermediate loop.
619  Within this sub-subsection only, the model state is stored  Within this sub-subsection only, parts of the model state is stored
620  at every timestep  to memory at every timestep
621  [i.e. every hour $ i=0,...,5$ corresponding to  [i.e. every hour $ i=0,...,5$ corresponding to
622  $ k_{i}^{lev1} = 66, 67, \ldots, 71 $].  $ k_{i}^{lev1} = 66, 67, \ldots, 71 $].
623  Thus, the  final state $ v_n = v_{k_{n}^{lev1}} $ is reached  The  final state $ v_n = v_{k_{n}^{lev1}} $ is reached
624  and the model state of all  proceeding timesteps along the last  and the model state of all preceding timesteps along the last
625  sub-subsections are available, enabling integration backwards  innermost subsection are available, enabling integration backwards
626  in time along the last sub-subsection.  in time along the last subsection.
627  Thus, the adjoint can be computed along this last  The adjoint can thus be computed along this last
628  sub-subsection $k_{n}^{lev2}$.  subsection $k_{n}^{lev2}$.
629  %  %
630  \end{itemize}  \end{itemize}
631  %  %
632  This procedure is repeated consecutively for each previous  This procedure is repeated consecutively for each previous
633  sub-subsection $k_{n-1}^{lev2}, \ldots, k_{1}^{lev2} $  subsection $k_{n-1}^{lev2}, \ldots, k_{1}^{lev2} $
634  carrying the adjoint computation to the initial time  carrying the adjoint computation to the initial time
635  of the subsection $k_{n}^{lev3}$.  of the subsection $k_{n}^{lev3}$.
636  Then, the procedure is repeated for the previous subsection  Then, the procedure is repeated for the previous subsection
# Line 627  $k_{1}^{lev3}$. Line 641  $k_{1}^{lev3}$.
641  For the full model trajectory of  For the full model trajectory of
642  $ n^{lev3} \cdot n^{lev2} \cdot n^{lev1} $ timesteps  $ n^{lev3} \cdot n^{lev2} \cdot n^{lev1} $ timesteps
643  the required storing of the model state was significantly reduced to  the required storing of the model state was significantly reduced to
644  $ n^{lev1} + n^{lev2} + n^{lev3} $  $ n^{lev2} + n^{lev3} $ to disk and roughly $ n^{lev1} $ to memory
645  [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
646  the model state was stored 13 times].  the model state was stored 7 times to disk and roughly 6 times
647    to memory].
648  This saving in memory comes at a cost of a required  This saving in memory comes at a cost of a required
649  3 full forward integrations of the model (one for each  3 full forward integrations of the model (one for each
650  checkpointing level).  checkpointing level).
651  The balance of storage vs. recomputation certainly depends  The optimal balance of storage vs. recomputation certainly depends
652  on the computing resources available.  on the computing resources available and may be adjusted by
653    adjusting the partitioning among the
654    $ n^{lev3}, \,\, n^{lev2}, \,\, n^{lev1} $.
655    
656  \begin{figure}[t!]  \begin{figure}[t!]
657  \begin{center}  \begin{center}
# Line 647  on the computing resources available. Line 664  on the computing resources available.
664  %\psfrag{v_kn^lev2}{\mathinfigure{v_{k_{n}^{lev2}}}}  %\psfrag{v_kn^lev2}{\mathinfigure{v_{k_{n}^{lev2}}}}
665  %\psfrag{v_k1^lev1}{\mathinfigure{v_{k_{1}^{lev1}}}}  %\psfrag{v_k1^lev1}{\mathinfigure{v_{k_{1}^{lev1}}}}
666  %\psfrag{v_kn^lev1}{\mathinfigure{v_{k_{n}^{lev1}}}}  %\psfrag{v_kn^lev1}{\mathinfigure{v_{k_{n}^{lev1}}}}
667  %\mbox{\epsfig{file=part5/checkpointing.eps, width=0.8\textwidth}}  %\mbox{\epsfig{file=s_autodiff/figs/checkpointing.eps, width=0.8\textwidth}}
668  \resizebox{5.5in}{!}{\includegraphics{part5/checkpointing.eps}}  \resizebox{5.5in}{!}{\includegraphics{s_autodiff/figs/checkpointing.eps}}
669  %\psfull  %\psfull
670  \end{center}  \end{center}
671  \caption{  \caption{
# Line 664  Schematic view of intermediate dump and Line 681  Schematic view of intermediate dump and
681  % \subsection{Error covariance estimate and Hessian matrix}  % \subsection{Error covariance estimate and Hessian matrix}
682  % \label{sec_hessian}  % \label{sec_hessian}
683    
684  \newpage  \newpage
685    
686  %**********************************************************************  %**********************************************************************
687  \section{AD-specific setup by example: sensitivity of carbon sequestration}  \section{TLM and ADM generation in general}
688  \label{sec_ad_setup_ex}  \label{sec_ad_setup_gen}
689    \begin{rawhtml}
690    <!-- CMIREDIR:sec_ad_setup_gen: -->
691    \end{rawhtml}
692  %**********************************************************************  %**********************************************************************
693    
694  The MITGCM has been adapted to enable AD using TAMC or TAF.  In this section we describe in a general fashion
695  The present description, therefore, is specific to the  the parts of the code that are relevant for automatic
696  use of TAMC or TAF as AD tool.  differentiation using the software tool TAF.
697  The following sections describe the steps which are necessary to  Modifications to use OpenAD are described in \ref{sec_ad_openad}.
698  generate a tangent linear or adjoint model of the MITGCM.  
699  We take as an example the sensitivity of carbon sequestration  \input{s_autodiff/text/doc_ad_the_model}
700  in the ocean.  
701  The AD-relevant hooks in the code are sketched in  The basic flow is depicted in \ref{fig:adthemodel}.
702  \ref{fig:adthemodel}, \ref{fig:adthemain}.  If CPP option \texttt{ALLOW\_AUTODIFF\_TAMC} is defined,
703    the driver routine
704  \subsection{Overview of the experiment}  {\it the\_model\_main}, instead of calling {\it the\_main\_loop},
705    invokes the adjoint of this routine, {\it adthe\_main\_loop}
706  We describe an adjoint sensitivity analysis of out-gassing from  (case \texttt{\#define ALLOW\_ADJOINT\_RUN}), or
707  the ocean into the atmosphere of a carbon-like tracer injected  the tangent linear of this routine {\it g\_the\_main\_loop}
708  into the ocean interior (see \cite{hil-eta:01}).  (case \texttt{\#define ALLOW\_TANGENTLINEAR\_RUN}),
709    which are the toplevel routines in terms of automatic differentiation.
710  \subsubsection{Passive tracer equation}  The routines {\it adthe\_main\_loop} or {\it g\_the\_main\_loop}
711    are generated by TAF.
712  For this work the MITGCM was augmented with a thermodynamically  It contains both the forward integration of the full model, the
713  inactive tracer, $C$. Tracer residing in the ocean  cost function calculation,
714  model surface layer is out-gassed according to a relaxation time scale,  any additional storing that is required for efficient checkpointing,
715  $\mu$. Within the ocean interior, the tracer is passively advected  and the reverse integration of the adjoint model.
716  by the ocean model currents. The full equation for the time evolution  
717  %  [DESCRIBE IN A SEPARATE SECTION THE WORKING OF THE TLM]
718  \begin{equation}  
719  \label{carbon_ddt}  In Fig. \ref{fig:adthemodel}
720  \frac{\partial C}{\partial t} \, = \,  the structure of {\it adthe\_main\_loop} has been strongly
721  -U\cdot \nabla C \, - \, \mu C \, + \, \Gamma(C) \,+ \, S  simplified to focus on the essentials; in particular, no checkpointing
722  \end{equation}  procedures are shown here.
723  %  Prior to the call of {\it adthe\_main\_loop}, the routine
724  also includes a source term $S$. This term  {\it ctrl\_unpack} is invoked to unpack the control vector
725  represents interior sources of $C$ such as would arise due to  or initialise the control variables.
726  direct injection.  Following the call of {\it adthe\_main\_loop},
727  The velocity term, $U$, is the sum of the  the routine {\it ctrl\_pack}
728  model Eulerian circulation and an eddy-induced velocity, the latter  is invoked to pack the control vector
729  parameterized according to Gent/McWilliams  (cf. Section \ref{section_ctrl}).
730  (\cite{gen-mcw:90, gen-eta:95}).  If gradient checks are to be performed, the option
731  The convection function, $\Gamma$, mixes $C$ vertically wherever the  {\tt ALLOW\_GRADIENT\_CHECK} is defined. In this case
732  fluid is locally statically unstable.  the driver routine {\it grdchk\_main} is called after
733    the gradient has been computed via the adjoint
734  The out-gassing time scale, $\mu$, in eqn. (\ref{carbon_ddt})  (cf. Section \ref{sec:ad_gradient_check}).
 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}  
 %  
735    
736  Below we describe the customizations of this files which are  %------------------------------------------------------------------
 specific to this experiment.  
737    
738  \subsubsection{File {\it .genmakerc}}  \subsection{General setup
739  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 ???.  
740    
741  \subsubsection{File {\it ECCO\_OPTIONS.h}}  In order to configure AD-related setups the following packages need
742    to be enabled:
743    {\it
744    \begin{table}[!ht]
745    \begin{tabular}{l}
746    autodiff \\
747    ctrl \\
748    cost \\
749    grdchk \\
750    \end{tabular}
751    \end{table}
752    }
753    The packages are enabled by adding them to your experiment-specific
754    configuration file
755    {\it packages.conf} (see Section ???).
756    
757  The CPP options of several AD-related packages are grouped  The following AD-specific CPP option files need to be customized:
 in this file:  
758  %  %
759  \begin{itemize}  \begin{itemize}
760  %  %
761  \item  \item {\it ECCO\_CPPOPTIONS.h} \\
762  Adjoint support package: {\it pkg/autodiff/} \\  This header file collects CPP options for the packages
763  This package contains hand-written adjoint code such as  {\it autodiff, cost, ctrl} as well as AD-unrelated options for
764  active file handling, flow directives for files which must not  the external forcing package {\it exf}.
765  be differentiated, and TAMC-specific header files. \\  \footnote{NOTE: These options are not set in their package-specific
766  \hspace*{4ex} {\tt \#define ALLOW\_AUTODIFF\_TAMC} \\  headers such as {\it COST\_CPPOPTIONS.h}, but are instead collected
767  defines TAMC-related features in the code. \\  in the single header file {\it ECCO\_CPPOPTIONS.h}.
768  \hspace*{4ex} {\tt \#define ALLOW\_TAMC\_CHECKPOINTING} \\  The package-specific header files serve as simple
769  enables the checkpointing feature of TAMC  placeholders at this point.}
770  (see Section \ref{???}).  %
771  In the present example a 3-level checkpointing is implemented.  \item {\it tamc.h} \\
772  The code contains the relevant store directives, common block  This header configures the splitting of the time stepping loop
773  and tape initializations, storing key computation,  w.r.t. the 3-level checkpointing (see section ???).
774  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}  
775  %  %
776  \end{itemize}  \end{itemize}
777    
778  \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}.  
779    
780  \subsubsection{File {\it tamc.h}}  \subsection{Building the AD code using TAF
781    \label{section_ad_build}}
782    
783  This routine contains the dimensions for TAMC checkpointing.  The build process of an AD code is very similar to building
784    the forward model. However, depending on which AD code one wishes
785    to generate, and on which AD tool is available (TAF or TAMC),
786    the following {\tt make} targets are available:
787    
788    \begin{table}[!ht]
789    {\footnotesize
790    \begin{tabular}{|ccll|}
791    \hline
792    ~ & {\it AD-target} & {\it output} & {\it description} \\
793    \hline
794    \hline
795    (1) & {\tt <MODE><TOOL>only} & {\tt <MODE>\_<TOOL>\_output.f}  &
796    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
797    ~ & ~ & ~ & no {\tt make} dependencies on {\tt .F .h} \\
798    ~ & ~ & ~ & useful for compiling on remote platforms \\
799    \hline
800    (2) & {\tt <MODE><TOOL>} & {\tt <MODE>\_<TOOL>\_output.f}  &
801    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
802    ~ & ~ & ~ & includes {\tt make} dependencies on {\tt .F .h} \\
803    ~ & ~ & ~ & i.e. input for $<$TOOL$>$ may be re-generated \\
804    \hline
805    (3) & {\tt <MODE>all} & {\tt mitgcmuv\_<MODE>}  &
806    generates code for $<$MODE$>$ using $<$TOOL$>$ \\
807    ~ & ~ & ~ & and compiles all code \\
808    ~ & ~ & ~ & (use of TAF is set as default) \\
809    \hline
810    \end{tabular}
811    }
812    \end{table}
813    %
814    Here, the following placeholders are used
815  %  %
816  \begin{itemize}  \begin{itemize}
817  %  %
818  \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}.  
819  %  %
820  \end{itemize}  \begin{itemize}
   
 The following parameters may be worth describing: \\  
821  %  %
822  \hspace*{4ex} {\tt isbyte} \\  \item {\tt TAF}
823  \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}  
824  %  %
 \begin{itemize}  
 \item [{\tt tamc}] {\tt  
 -input <variable names>  
 -output <variable name> -r4 ... \\  
 -toplevel <S/R name> -reverse <file names>  
 }  
825  \end{itemize}  \end{itemize}
826  %  %
827    \item $<$MODE$>$
828    %
829  \begin{itemize}  \begin{itemize}
830  %  %
831  \item {\tt -toplevel <S/R name>} \\  \item {\tt ad} generates the adjoint model (ADM)
832  Name of the toplevel routine, with respect to which the  \item {\tt ftl} generates the tangent linear model (TLM)
833  control flow analysis is performed.  \item {\tt svd} generates both ADM and TLM for \\
834  %  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.  
835  %  %
836  \item {\tt -r4} \\  \end{itemize}
 ~  
837  %  %
838  \end{itemize}  \end{itemize}
839    
840    For example, to generate the adjoint model using TAF after routines ({\tt .F})
841    or headers ({\tt .h}) have been modified, but without compilation,
842    type {\tt make adtaf};
843    or, to generate the tangent linear model using TAMC without
844    re-generating the input code, type {\tt make ftltamconly}.
845    
 \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}}  
846    
847  \paragraph{File {\it salt.bin, theta.bin}}  A typical full build process to generate the ADM via TAF would
848    look like follows:
849  \paragraph{File {\it SSS.bin, SST.bin}}  \begin{verbatim}
850    % mkdir build
851  \paragraph{File {\it pickup*}}  % cd build
852    % ../../../tools/genmake2 -mods=../code_ad
853  \subsection{Compiling the model and its adjoint}  % make depend
854    % make adall
855    \end{verbatim}
856    
857  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.  
858    
859  In the following we describe the build process step by step,  \subsection{The AD build process in detail
860  assuming you are in the directory {\tt bin/}.  \label{section_ad_build_detail}}
 A summary of steps to follow is given at the end.  
861    
862  \paragraph{Adjoint code generation and compilation -- step by step}  The {\tt make <MODE>all} target consists of the following procedures:
863    
864  \begin{enumerate}  \begin{enumerate}
865  %  %
866  \item  \item
867  {\tt ln -s ../verification/???/code/.genmakerc .} \\  A header file {\tt AD\_CONFIG.h} is generated which contains a CPP option
868  {\tt ln -s ../verification/???/code/*.[Fh] .} \\  on which code ought to be generated. Depending on the {\tt make} target,
869  Link your customized genmake options, header files,  the contents is one of the following:
870  and modified code to the compile directory.  \begin{itemize}
 %  
871  \item  \item
872  {\tt ../tools/genmake -makefile} \\  {\tt \#define ALLOW\_ADJOINT\_RUN}
 Generate your Makefile (cf. Section ???).  
 %  
873  \item  \item
874  {\tt make depend} \\  {\tt \#define ALLOW\_TANGENTLINEAR\_RUN}
 Dependency analysis for the CPP pre-compiler (cf. Section ???).  
 %  
875  \item  \item
876  {\tt make small\_f} \\  {\tt \#define ALLOW\_ECCO\_OPTIMIZATION}
877  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.  
878  %  %
879  \item  \item
880  {\tt cd ../adjoint} \\  A single file {\tt <MODE>\_input\_code.f} is concatenated
881  {\tt make adtaf} or {\tt make adtamc} \\  consisting of all {\tt .f} files that are part of the list {\bf AD\_FILES}
882  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}  
883  %  %
884  \item  \item
885  The initial template file {\it adjoint\_model.F} which is part  The AD tool is invoked with the {\tt <MODE>\_<TOOL>\_FLAGS}.
886  of the compiling list created by {\it genmake} is restored.  The default AD tool flags in {\tt genmake2} can be overrwritten by
887    an {\tt adjoint\_options} file (similar to the platform-specific
888    {\tt build\_options}, see Section ???.
889    The AD tool writes the resulting AD code into the file
890    {\tt <MODE>\_input\_code\_ad.f}
891  %  %
892  \item  \item
893  All Fortran routines {\tt *.f} in {\tt bin/} are  A short sed script {\tt adjoint\_sed} is applied to
894  concatenated into a single file (it's current name is  {\tt <MODE>\_input\_code\_ad.f}
895  {\it tamc\_code.f}).  to reinstate {\bf myThid} into the CALL argument list of active file I/O.
896    The result is written to file {\tt <MODE>\_<TOOL>\_output.f}.
897  %  %
898  \item  \item
899  Adjoint code is generated by TAMC or TAF.  All routines are compiled and an executable is generated
900  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.  
901  %  %
902  \end{enumerate}  \end{enumerate}
903    
904    \subsubsection{The list AD\_FILES and {\tt .list} files}
905    
906    Not all routines are presented to the AD tool.
907    Routines typically hidden are diagnostics routines which
908    do not influence the cost function, but may create
909    artificial flow dependencies such as I/O of active variables.
910    
911    {\tt genmake2} generates a list (or variable) {\bf AD\_FILES}
912    which contains all routines that are shown to the AD tool.
913    This list is put together from all files with suffix {\tt .list}
914    that {\tt genmake2} finds in its search directories.
915    The list file for the core MITgcm routines is in {\tt model/src/}
916    is called {\tt model\_ad\_diff.list}.
917    Note that no wrapper routine is shown to TAF. These are either
918    not visible at all to the AD code, or hand-written AD code
919    is available (see next section).
920    
921    Each package directory contains its package-specific
922    list file {\tt <PKG>\_ad\_diff.list}. For example,
923    {\tt pkg/ptracers/} contains the file {\tt ptracers\_ad\_diff.list}.
924    Thus, enabling a package will automatically extend the
925    {\bf AD\_FILES} list of {\tt genmake2} to incorporate the
926    package-specific routines.
927    Note that you will need to regenerate the {\tt Makefile} if
928    you enable a package (e.g. by adding it to {\tt packages.conf})
929    and a {\tt Makefile} already exists.
930    
931    \subsubsection{The list AD\_FLOW\_FILES and {\tt .flow} files}
932    
933    TAMC and TAF can evaluate user-specified directives
934    that start with a specific syntax ({\tt CADJ}, {\tt C\$TAF}, {\tt !\$TAF}).
935    The main categories of directives are STORE directives and
936    FLOW directives. Here, we are concerned with flow directives,
937    store directives are treated elsewhere.
938    
939    Flow directives enable the AD tool to evaluate how it should treat
940    routines that are 'hidden' by the user, i.e. routines which are
941    not contained in the {\bf AD\_FILES} list (see previous section),
942    but which are called in part of the code that the AD tool does see.
943    The flow directive tell the AD tool
944  %  %
945  \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.  
946  %  %
947  \item  \item which subroutine arguments are input/output
948  {\tt cd ../bin} \\  \item which subroutine arguments are active
949  {\tt make} \\  \item which subroutine arguments are required to compute the cost
950  The file {\it adjoint\_model.F} now contains the full adjoint code.  \item which subroutine arguments are dependent
 All routines are now compiled.  
951  %  %
952  \end{enumerate}  \end{itemize}
953    %
954    The syntax for the flow directives can be found in the
955    AD tool manuals.
956    
957  \paragraph{Adjoint code generation and compilation -- summary}  {\tt genmake2} generates a list (or variable) {\bf AD\_FLOW\_FILES}
958  ~ \\  which contains all files with suffix{\tt .flow} that it finds
959    in its search directories.
960    The flow directives for the core MITgcm routines of
961    {\tt eesupp/src/} and {\tt model/src/}
962    reside in {\tt pkg/autodiff/}.
963    This directory also contains hand-written adjoint code
964    for the MITgcm WRAPPER (section \ref{chap:sarch}).
965    
966    Flow directives for package-specific routines are contained in
967    the corresponding package directories in the file
968    {\tt <PKG>\_ad.flow}, e.g. ptracers-specific directives are in
969    {\tt ptracers\_ad.flow}.
970    
971    \subsubsection{Store directives for 3-level checkpointing}
972    
973    The storing that is required at each period of the
974    3-level checkpointing is controled by three
975    top-level headers.
976    
977  \[  \begin{verbatim}
978  \boxed{  do ilev_3 = 1, nchklev_3
979  \begin{split}  #  include ``checkpoint_lev3.h''
980   ~ & \mbox{\tt cd bin} \\     do ilev_2 = 1, nchklev_2
981   ~ & \mbox{\tt ln -s ../verification/my\_experiment/code/.genmakerc .} \\  #     include ``checkpoint_lev2.h''
982   ~ & \mbox{\tt ln -s ../verification/my\_experiment/code/*.[Fh] .} \\        do ilev_1 = 1, nchklev_1
983   ~ & \mbox{\tt ../tools/genmake -makefile} \\  #        include ``checkpoint_lev1.h''
984   ~ & \mbox{\tt make depend} \\  
985   ~ & \mbox{\tt make small\_f} \\  ...
986   ~ & \mbox{\tt cd ../adjoint} \\  
987   ~ & \mbox{\tt make adtaf <OR: make adtamc>} \\        end do
988   ~ & \mbox{\tt make adchange} \\     end do
989   ~ & \mbox{\tt cd ../bin} \\  end do
990   ~ & \mbox{\tt make} \\  \end{verbatim}
 \end{split}  
 }  
 \]  
991    
992  \newpage  All files {\tt checkpoint\_lev?.h} are contained in directory
993    {\tt pkg/autodiff/}.
994    
 %**********************************************************************  
 \section{TLM and ADM generation in general}  
 \label{sec_ad_setup_gen}  
 %**********************************************************************  
995    
996  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.  
997    
 \begin{figure}[b!]  
 \input{part5/doc_ad_the_model}  
 \caption{~}  
 \label{fig:adthemodel}  
 \end{figure}  
998    
999  The basic flow is depicted in \ref{fig:adthemodel}.  \subsubsection{Hand-written adjoint code}
1000  If the option {\tt ALLOW\_AUTODIFF\_TAMC} is defined, the driver routine  
1001  {\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}).  
1002    
1003  \subsection{The cost function (dependent variable)  \subsection{The cost function (dependent variable)
1004  \label{section_cost}}  \label{section_cost}}
# Line 1293  the gradient has been computed via the a Line 1006  the gradient has been computed via the a
1006  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}.
1007  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
1008  $ {\cal J}(\vec{u}) \, = \, {\cal J}(M(\vec{u})) $.  $ {\cal J}(\vec{u}) \, = \, {\cal J}(M(\vec{u})) $.
1009  The input is referred to as the  The input are referred to as the
1010  {\sf independent variables} or {\sf control variables}.  {\sf independent variables} or {\sf control variables}.
1011  All aspects relevant to the treatment of the cost function $ {\cal J} $  All aspects relevant to the treatment of the cost function $ {\cal J} $
1012  (parameter setting, initialization, accumulation,  (parameter setting, initialization, accumulation,
1013  final evaluation), are controlled by the package {\it pkg/cost}.  final evaluation), are controlled by the package {\it pkg/cost}.
1014    The aspects relevant to the treatment of the independent variables
1015    are controlled by the package {\it pkg/ctrl} and will be treated
1016    in the next section.
1017    
1018  \begin{figure}[h!]  \input{s_autodiff/text/doc_cost_flow}
1019  \input{part5/doc_cost_flow}  
1020  \caption{~}  \subsubsection{Enabling the package}
 \label{fig:costflow}  
 \end{figure}  
1021    
 \subsubsection{genmake and CPP options}  
 %  
 \begin{itemize}  
 %  
 \item  
1022  \fbox{  \fbox{
1023  \begin{minipage}{12cm}  \begin{minipage}{12cm}
1024  {\it genmake}, {\it CPP\_OPTIONS.h}, {\it ECCO\_CPPOPTIONS.h}  {\it packages.conf}, {\it ECCO\_CPPOPTIONS.h}
1025  \end{minipage}  \end{minipage}
1026  }  }
1027  \end{itemize}  \begin{itemize}
 %  
 The directory {\it pkg/cost} can be included to the  
 compile list in 3 different ways (cf. Section \ref{???}):  
1028  %  %
1029  \begin{enumerate}  \item
1030    The package is enabled by adding {\it cost} to your file {\it packages.conf}
1031    (see Section ???)
1032  %  %
1033  \item {\it genmake}: \\  \item
1034  Change the default settings in the file {\it genmake} by adding  
1035  {\bf cost} to the {\bf enable} list (not recommended).  
1036  %  \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}.  
1037  %  %
1038  \end{enumerate}  
1039    N.B.: In general the following packages ought to be enabled
1040    simultaneously: {\it autodiff, cost, ctrl}.
1041  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}.
1042  Each specific cost function contribution has its own option.  Each specific cost function contribution has its own option.
1043  For the present example the option is {\bf ALLOW\_COST\_TRACER}.  For the present example the option is {\bf ALLOW\_COST\_TRACER}.
1044  All cost-specific options are set in {\it ECCO\_CPPOPTIONS.h}  All cost-specific options are set in {\it ECCO\_CPPOPTIONS.h}
1045  Since the cost function is usually used in conjunction with  Since the cost function is usually used in conjunction with
1046  automatic differentiation, the CPP option  automatic differentiation, the CPP option
1047  {\bf ALLOW\_ADJOINT\_RUN} should be defined  {\bf ALLOW\_ADJOINT\_RUN} (file {\it CPP\_OPTIONS.h}) and
1048  (file {\it CPP\_OPTIONS.h}).  {\bf ALLOW\_AUTODIFF\_TAMC} (file {\it ECCO\_CPPOPTIONS.h})
1049    should be defined.
1050    
1051  \subsubsection{Initialization}  \subsubsection{Initialization}
1052  %  %
1053  The initialization of the {\it cost} package is readily enabled  The initialization of the {\it cost} package is readily enabled
1054  as soon as the CPP option {\bf ALLOW\_ADJOINT\_RUN} is defined.  as soon as the CPP option {\bf ALLOW\_COST} is defined.
1055  %  %
1056  \begin{itemize}  \begin{itemize}
1057  %  %
# Line 1402  Within this 'driver' routine, S/R are ca Line 1105  Within this 'driver' routine, S/R are ca
1105  the chosen cost function contributions.  the chosen cost function contributions.
1106  In the present example ({\bf ALLOW\_COST\_TRACER}),  In the present example ({\bf ALLOW\_COST\_TRACER}),
1107  S/R {\it cost\_tracer} is called.  S/R {\it cost\_tracer} is called.
1108  It accumulates {\bf objf\_tracer} according to eqn. (\ref{???}).  It accumulates {\bf objf\_tracer} according to eqn. (ref:ask-the-author).
1109  %  %
1110  \subsubsection{Finalize all contributions}  \subsubsection{Finalize all contributions}
1111  %  %
# Line 1422  from each contribution and sums over all Line 1125  from each contribution and sums over all
1125  \begin{equation}  \begin{equation}
1126  {\cal J} \, = \,  {\cal J} \, = \,
1127  {\rm fc} \, = \,  {\rm fc} \, = \,
1128  {\rm mult\_tracer} \sum_{bi,\,bj}^{nSx,\,nSy}  {\rm mult\_tracer} \sum_{\text{global sum}} \sum_{bi,\,bj}^{nSx,\,nSy}
1129  {\rm objf\_tracer}(bi,bj) \, + \, ...  {\rm objf\_tracer}(bi,bj) \, + \, ...
1130  \end{equation}  \end{equation}
1131  %  %
1132  The total cost function {\bf fc} will be the  The total cost function {\bf fc} will be the
1133  'dependent' variable in the argument list for TAMC, i.e.  'dependent' variable in the argument list for TAF, i.e.
1134  \begin{verbatim}  \begin{verbatim}
1135  tamc -output 'fc' ...  taf -output 'fc' ...
1136  \end{verbatim}  \end{verbatim}
1137    
1138  %%%% \end{document}  %%%% \end{document}
1139    
1140  \begin{figure}  \input{s_autodiff/text/doc_ad_the_main}
 \input{part5/doc_ad_the_main}  
 \caption{~}  
 \label{fig:adthemain}  
 \end{figure}  
1141    
1142  \subsection{The control variables (independent variables)  \subsection{The control variables (independent variables)
1143  \label{section_ctrl}}  \label{section_ctrl}}
# Line 1458  All aspects relevant to the treatment of Line 1157  All aspects relevant to the treatment of
1157  (parameter setting, initialization, perturbation)  (parameter setting, initialization, perturbation)
1158  are controlled by the package {\it pkg/ctrl}.  are controlled by the package {\it pkg/ctrl}.
1159    
1160  \begin{figure}[h!]  \input{s_autodiff/text/doc_ctrl_flow}
 \input{part5/doc_ctrl_flow}  
 \caption{~}  
 \label{fig:ctrlflow}  
 \end{figure}  
1161    
1162  \subsubsection{genmake and CPP options}  \subsubsection{genmake and CPP options}
1163  %  %
# Line 1478  are controlled by the package {\it pkg/c Line 1173  are controlled by the package {\it pkg/c
1173  %  %
1174  To enable the directory to be included to the compile list,  To enable the directory to be included to the compile list,
1175  {\bf ctrl} has to be added to the {\bf enable} list in  {\bf ctrl} has to be added to the {\bf enable} list in
1176  {\it .genmakerc} (or {\it genmake} itself).  {\it .genmakerc} or in {\it genmake} itself (analogous to {\it cost}
1177    package, cf. previous section).
1178  Each control variable is enabled via its own CPP option  Each control variable is enabled via its own CPP option
1179  in {\it ECCO\_CPPOPTIONS.h}.  in {\it ECCO\_CPPOPTIONS.h}.
1180    
# Line 1519  and their gradients: {\it ctrl\_unpack} Line 1215  and their gradients: {\it ctrl\_unpack}
1215  \\  \\
1216  %  %
1217  Two important issues related to the handling of the control  Two important issues related to the handling of the control
1218  variables in the MITGCM need to be addressed.  variables in MITgcm need to be addressed.
1219  First, in order to save memory, the control variable arrays  First, in order to save memory, the control variable arrays
1220  are not kept in memory, but rather read from file and added  are not kept in memory, but rather read from file and added
1221  to the initial fields during the model initialization phase.  to the initial fields during the model initialization phase.
# Line 1551  and gradient are generated and initialis Line 1247  and gradient are generated and initialis
1247  %  %
1248  The dependency flow for differentiation w.r.t. the controls  The dependency flow for differentiation w.r.t. the controls
1249  starts with adding a perturbation onto the input variable,  starts with adding a perturbation onto the input variable,
1250  thus defining the independent or control variables for TAMC.  thus defining the independent or control variables for TAF.
1251  Three types of controls may be considered:  Three types of controls may be considered:
1252  %  %
1253  \begin{itemize}  \begin{itemize}
# Line 1572  temperature and salinity are initialised Line 1268  temperature and salinity are initialised
1268  a perturbation anomaly is added to the field in S/R  a perturbation anomaly is added to the field in S/R
1269  {\it ctrl\_map\_ini}  {\it ctrl\_map\_ini}
1270  %  %
1271    %\begin{eqnarray}
1272  \begin{equation}  \begin{equation}
1273  \begin{split}  \begin{aligned}
1274  u         & = \, u_{[0]} \, + \, \Delta u \\  u         & = \, u_{[0]} \, + \, \Delta u \\
1275  {\bf tr1}(...) & = \, {\bf tr1_{ini}}(...) \, + \, {\bf xx\_tr1}(...)  {\bf tr1}(...) & = \, {\bf tr1_{ini}}(...) \, + \, {\bf xx\_tr1}(...)
1276  \label{perturb}  \label{perturb}
1277  \end{split}  \end{aligned}
1278  \end{equation}  \end{equation}
1279    %\end{eqnarray}
1280  %  %
1281  {\bf xx\_tr1} is a 3-dim. global array  {\bf xx\_tr1} is a 3-dim. global array
1282  holding the perturbation. In the case of a simple  holding the perturbation. In the case of a simple
1283  sensitivity study this array is identical to zero.  sensitivity study this array is identical to zero.
1284  However, it's specification is essential in the context  However, it's specification is essential in the context
1285  of automatic differentiation since TAMC  of automatic differentiation since TAF
1286  treats the corresponding line in the code symbolically  treats the corresponding line in the code symbolically
1287  when determining the differentiation chain and its origin.  when determining the differentiation chain and its origin.
1288  Thus, the variable names are part of the argument list  Thus, the variable names are part of the argument list
1289  when calling TAMC:  when calling TAF:
1290  %  %
1291  \begin{verbatim}  \begin{verbatim}
1292  tamc -input 'xx_tr1 ...' ...  taf -input 'xx_tr1 ...' ...
1293  \end{verbatim}  \end{verbatim}
1294  %  %
1295  Now, as mentioned above, the MITGCM avoids maintaining  Now, as mentioned above, MITgcm avoids maintaining
1296  an array for each control variable by reading the  an array for each control variable by reading the
1297  perturbation to a temporary array from file.  perturbation to a temporary array from file.
1298  To ensure the symbolic link to be recognized by TAMC, a scalar  To ensure the symbolic link to be recognized by TAF, a scalar
1299  dummy variable {\bf xx\_tr1\_dummy} is introduced  dummy variable {\bf xx\_tr1\_dummy} is introduced
1300  and an 'active read' routine of the adjoint support  and an 'active read' routine of the adjoint support
1301  package {\it pkg/autodiff} is invoked.  package {\it pkg/autodiff} is invoked.
1302  The read-procedure is tagged with the variable  The read-procedure is tagged with the variable
1303  {\bf xx\_tr1\_dummy} enabling TAMC to recognize the  {\bf xx\_tr1\_dummy} enabling TAF to recognize the
1304  initialization of the perturbation.  initialization of the perturbation.
1305  The modified call of TAMC thus reads  The modified call of TAF thus reads
1306  %  %
1307  \begin{verbatim}  \begin{verbatim}
1308  tamc -input 'xx_tr1_dummy ...' ...  taf -input 'xx_tr1_dummy ...' ...
1309  \end{verbatim}  \end{verbatim}
1310  %  %
1311  and the modified operation to (\ref{perturb})  and the modified operation to (\ref{perturb})
# Line 1622  in the code takes on the form Line 1320  in the code takes on the form
1320  %  %
1321  Note, that reading an active variable corresponds  Note, that reading an active variable corresponds
1322  to a variable assignment. Its derivative corresponds  to a variable assignment. Its derivative corresponds
1323  to a write statement of the adjoint variable.  to a write statement of the adjoint variable, followed by
1324    a reset.
1325  The 'active file' routines have been designed  The 'active file' routines have been designed
1326  to support active read and corresponding adjoint active write  to support active read and corresponding adjoint active write
1327  operations (and vice versa).  operations (and vice versa).
# Line 1739  at intermediate times can be written usi Line 1438  at intermediate times can be written usi
1438  {\it addummy\_in\_stepping}.  {\it addummy\_in\_stepping}.
1439  This routine is part of the adjoint support package  This routine is part of the adjoint support package
1440  {\it pkg/autodiff} (cf.f. below).  {\it pkg/autodiff} (cf.f. below).
1441    The procedure is enabled using via the CPP-option
1442    {\bf ALLOW\_AUTODIFF\_MONITOR} (file {\it ECCO\_CPPOPTIONS.h}).
1443  To be part of the adjoint code, the corresponding S/R  To be part of the adjoint code, the corresponding S/R
1444  {\it dummy\_in\_stepping} has to be called in the forward  {\it dummy\_in\_stepping} has to be called in the forward
1445  model (S/R {\it the\_main\_loop}) at the appropriate place.  model (S/R {\it the\_main\_loop}) at the appropriate place.
1446    The adjoint common blocks are extracted from the adjoint code
1447    via the header file {\it adcommon.h}.
1448    
1449  {\it dummy\_in\_stepping} is essentially empty,  {\it dummy\_in\_stepping} is essentially empty,
1450  the corresponding adjoint routine is hand-written rather  the corresponding adjoint routine is hand-written rather
# Line 1768  the common blocks Line 1471  the common blocks
1471  {\bf /adtr1\_r/}, {\bf /adffields/},  {\bf /adtr1\_r/}, {\bf /adffields/},
1472  which have been extracted from the adjoint code to enable  which have been extracted from the adjoint code to enable
1473  access to the adjoint variables.  access to the adjoint variables.
1474    
1475    {\bf WARNING:} If the structure of the common blocks
1476    {\bf /dynvars\_r/}, {\bf /dynvars\_cd/}, etc., changes
1477    similar changes will occur in the adjoint common blocks.
1478    Therefore, consistency between the TAMC-generated common blocks
1479    and those in {\it adcommon.h} have to be checked.
1480  %  %
1481  \end{itemize}  \end{itemize}
1482    
# Line 1782  The gradient $ \nabla _{u}{\cal J} |_{u_ Line 1491  The gradient $ \nabla _{u}{\cal J} |_{u_
1491  with the value of the cost function itself $ {\cal J}(u_{[k]}) $  with the value of the cost function itself $ {\cal J}(u_{[k]}) $
1492  at iteration step $ k $ serve  at iteration step $ k $ serve
1493  as input to a minimization routine (e.g. quasi-Newton method,  as input to a minimization routine (e.g. quasi-Newton method,
1494  conjugate gradient, ... \cite{gil_lem:89})  conjugate gradient, ... \cite{gil-lem:89})
1495  to compute an update in the  to compute an update in the
1496  control variable for iteration step $k+1$  control variable for iteration step $k+1$
1497  \[  \[
# Line 1793  u_{[k+1]} \, = \,  u_{[0]} \, + \, \Delt Line 1502  u_{[k+1]} \, = \,  u_{[0]} \, + \, \Delt
1502  $ u_{[k+1]} $ then serves as input for a forward/adjoint run  $ u_{[k+1]} $ then serves as input for a forward/adjoint run
1503  to determine $ {\cal J} $ and $ \nabla _{u}{\cal J} $ at iteration step  to determine $ {\cal J} $ and $ \nabla _{u}{\cal J} $ at iteration step
1504  $ k+1 $.  $ k+1 $.
1505  Tab. \ref{???} sketches the flow between forward/adjoint model  Tab. ref:ask-the-author sketches the flow between forward/adjoint model
1506  and the minimization routine.  and the minimization routine.
1507    
1508    {\scriptsize
1509  \begin{eqnarray*}  \begin{eqnarray*}
 \scriptsize  
1510  \begin{array}{ccccc}  \begin{array}{ccccc}
1511  u_{[0]} \,\, ,  \,\, \Delta u_{[k]}    & ~ & ~ & ~ & ~ \\  u_{[0]} \,\, ,  \,\, \Delta u_{[k]}    & ~ & ~ & ~ & ~ \\
1512  {\Big\downarrow}  {\Big\downarrow}
# Line 1848  ad \, v_{[k]} (\delta {\cal J}) = Line 1557  ad \, v_{[k]} (\delta {\cal J}) =
1557   ~ & ~ & ~ & ~ & \Delta u_{[k+1]} \\   ~ & ~ & ~ & ~ & \Delta u_{[k+1]} \\
1558  \end{array}  \end{array}
1559  \end{eqnarray*}  \end{eqnarray*}
1560    }
1561    
1562  The routines {\it ctrl\_unpack} and {\it ctrl\_pack} provide  The routines {\it ctrl\_unpack} and {\it ctrl\_pack} provide
1563  the link between the model and the minimization routine.  the link between the model and the minimization routine.
1564  As described in Section \ref{???}  As described in Section ref:ask-the-author
1565  the {\it unpack} and {\it pack} routines read and write  the {\it unpack} and {\it pack} routines read and write
1566  control and gradient {\it vectors} which are compressed  control and gradient {\it vectors} which are compressed
1567  to contain only wet points, in addition to the full  to contain only wet points, in addition to the full
# Line 1913  to {\it adxx\_...$<$k$>$}, again via the Line 1623  to {\it adxx\_...$<$k$>$}, again via the
1623  Finally, {\it ctrl\_pack} collects all adjoint files  Finally, {\it ctrl\_pack} collects all adjoint files
1624  and writes them to the compressed vector file  and writes them to the compressed vector file
1625  {\bf vector\_grad\_$<$k$>$}.  {\bf vector\_grad\_$<$k$>$}.
   
 \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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